Adaptive user interfaces for brain computer interface systems

Abstract

The present disclosure relates to systems and method for adapting a brain-computer interface to a user. In some aspects, the method includes providing an electronic user interface of a brain-computer interface configured to interact with an electronic device using a plurality of electronic control switches selectable using a neural activity of the user. The electronic user interface may be configured to increase or decrease a complexity level of a display of one or more of the plurality electronic control switches displayed by the user interface. The method may include adjusting the complexity level of the display based on monitoring the user, monitoring electronic testing activity of the user, or monitoring parameters associated with the user to establish an ability level of the user.

Description

Attorney Docket No.: SYNC-N-Z054-00-WOADAPTIVE USER INTERFACES FOR BRAIN-COMPUTER INTERFACE SYSTEMSCROSS REFERENCE TO REEATED APPLICATIONS

[0001] This Patent Application claims the benefit of U.S. Patent Application No.19 / 578,702 by GANGJEE et. al., entitled “ADAPTIVE USER INTERFACES FOR BRAINCOMPUTER INTERFACE SYSTEMS,” filed March 25, 2026, which claims priority to U.S. Provisional Patent Application No. 63 / 778,158 by GANGIEE et. al., entitled “ADAPTIVE USER INTERFACES FOR BRAIN COMPUTER INTERFACE SYSTEMS,” filed March 26, 2025, each of which is assigned to the assignee hereof and expressly incorporated herein.TECHNICAL FIELD

[0002] Methods and systems for adapting a user interface to improve the ability of an individual to use a brain-computer interface (BCI) system.DESCRIPTION OF THE RELATED TECHNOLOGY

[0003] The availability of brain-computer interface (BCI) systems has improved the ability of individuals to regain lost independence, including the ability to communicate and interact with their environment with increased autonomy. BCI systems allow users to provide instructions to electronic devices using endogenous signals, exogenous signals, or a combination of signals to interact with electronic devices associated with the BCI system. An endogenous signal may be a signal that the individual generates internally, such as signals relating to the neural activity of the individual. Such neural signals can be detected by sensors that measure electrical impulses produced when the individual generates a thought, moves a muscle (either through actual movement or imagined movement), or engages in other neural activity. Exogenous signals include any signal that is measured or generated externally to the individual, such as signals generated when the individual takes an action. For example, exogenous signals can include a signal generated when the individual triggers an external mechanism or electronic device (e.g., a mouse click, screen contact / tap, keyboard click, voice command, etc.), a signal generated by an inertial sensor that uses inertia to detect physical movement of a body part of the individual, a signal received using a camera-type device that detects movement of the individual (e.g., an eye movement detector, a body movement detector, etc.), sip and puff controls (typically used for wheelchairs), etc.

[0004] People with full or partial paralysis, neurological disabilities, and muscular disorders may be limited in their use of user interfaces, such as touchscreens, mice, or voicebased interfaces. While some user interfaces for BCI systems have overcome these difficultiesAttorney Docket No.: SYNC-N-Z054-00-WOby allowing user control via exogenous or endogenous signals, even these user interfaces are limited. There is currently no standardization or consensus on reliable user interface configurations for BCI systems, and default user interfaces provided with current BCI systems are likely to be inappropriate for all potential users and use cases. Some users may have difficulty navigating complex user interfaces and may grow fatigued and frustrated, ultimately discouraging them from using BCI systems. More sophisticated users may find simpler user interfaces insufficiently sophisticated and lacking options for quickly engaging with BCI systems. There is also a variability among users in their BCI literacy. BCI literacy refers to an individual’s proficiency in effectively operating BCI systems, which enable direct communication between the brain and external devices. This concept encompasses the ability to generate distinguishable brain signals, comprehend system feedback, and adapt to the BCI’s operational protocols. A significant challenge in the BCI field is the phenomenon termed “BCI illiteracy,” where different users achieve adequate control over BCI systems within different time frames and / or over more complex or less complex BCI systems. Factors Influencing BCI Literacy may include an individual’s unique brain signal patterns that can affect the BCI system’s ability to accurately interpret user intentions. Another factor may be the effectiveness of training methods, with tailored approaches potentially enhancing BCI literacy. Another factor may be the BCI system design: user-friendly interfaces and adaptive algorithms can mitigate some challenges associated with BCI illiteracy.

[0005] The needs of BCI system users may change over time as their condition progresses or as they become more competent using BCI interface systems, necessitating new user interface designs throughout the lifetime of a BCI system. These problems are exacerbated because many users of BCI systems have difficulty communicating their abilities and desire for modified user interfaces. To solve this problem, BCI system providers may enlist trained professionals, such as field clinical engineers, to adjust the user interface of BCI systems. However, training and deploying field clinical engineers could be unavailable, inconvenient, labor-intensive, and / or expensive, and engineers often rely on their subjective experience when modifying user interfaces rather than quantitative information about a particular user’s ability and needs.SUMMARY

[0006] The present disclosure includes systems and methods for providing adaptive user interfaces for assisting individuals using BCI systems. Such user interface may increase users’ engagement with BCI systems, reduce user fatigue, and improve users’ ability to communicate and interact with the world around them using BCI systems. The systems, methods, andAttorney Docket No.: SYNC-N-Z054-00-WOdevices of this disclosure each have several innovative aspects, no single one of which is solely responsible for the desirable attributes disclosed herein. The following is a summary of some non-limiting aspects of the disclosure:

[0007] A method of adapting a brain-computer interface to a user is described. The method may include providing a display on an electronic user interface operative with the braincomputer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display, providing an electronic testing activity for the neural activity on the electronic user interface, and adjusting the complexity level of the display based on a result of the electronic testing activity.

[0008] An apparatus is described. The apparatus may include a processing system that includes processor circuitry and memory circuitry that stores code. The processing system may be configured to cause the apparatus to provide a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display, provide an electronic testing activity for the neural activity on the electronic user interface, and adjust the complexity level of the display based on a result of the electronic testing activity.

[0009] Another apparatus is described. The apparatus may include means for providing a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display, means for providing an electronic testing activity for the neural activity on the electronic user interface, and means for adjusting the complexity level of the display based on a result of the electronic testing activity.

[0010] A non-transitory computer-readable medium storing code is described. The code may include instructions executable by one or more processors to provide a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display, provide an electronic testing activity for the neural activity on the electronic user interface, and adjust the complexity level of the display based on a result of the electronic testing activity.

[0011] Another method of adapting a brain-computer interface to a user is described. The method may include providing a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic controlAttorney Docket No.: SYNC-N-Z054-00-WOswitches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display, monitoring the user while engaging the electronic user interface to determine an ability level of the user to interact with the electronic user interface using the neural activity, and adjusting the complexity level of the set of multiple electronic control switches displayed by the electronic user interface based on the ability level of the user.

[0012] An apparatus is described. The apparatus may include a processing system that includes processor circuitry and memory circuitry that stores code. The processing system may be configured to cause the apparatus to provide a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display, monitor the user while engaging the electronic user interface to determine an ability level of the user to interact with the electronic user interface using the neural activity, and adjust the complexity level of the set of multiple electronic control switches displayed by the electronic user interface based on the ability level of the user.

[0013] Another apparatus is described. The apparatus may include means for providing a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display, means for monitoring the user while engaging the electronic user interface to determine an ability level of the user to interact with the electronic user interface using the neural activity, and means for adjusting the complexity level of the set of multiple electronic control switches displayed by the electronic user interface based on the ability level of the user.

[0014] A non-transitory computer-readable medium storing code is described. The code may include instructions executable by one or more processors to provide a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display, monitor the user while engaging the electronic user interface to determine an ability level of the user to interact with the electronic user interface using the neural activity, and adjust the complexity level of the set of multiple electronic control switches displayed by the electronic user interface based on the ability level of the user.

[0015] Another method of adapting an interface to a user is described. The method may include providing an electronic user interface for interacting with an electronic device using a set of multiple electronic control switches displayed by the electronic user interface, where theAttorney Docket No.: SYNC-N-Z054-00-WOelectronic user interface can adjust a complexity level of a display of one or more of the set of multiple electronic control switches, monitoring a parameter associated with a user when the user engages the electronic user interface, and adjusting the complexity level of the set of multiple electronic control switches displayed based on the parameter associated with the user.

[0016] An apparatus is described. The apparatus may include a processing system that includes processor circuitry and memory circuitry that stores code. The processing system may be configured to cause the apparatus to provide an electronic user interface for interacting with an electronic device using a set of multiple electronic control switches displayed by the electronic user interface, where the electronic user interface can adjust a complexity level of a display of one or more of the set of multiple electronic control switches, monitor a parameter associated with a user when the user engages the electronic user interface, and adjust the complexity level of the set of multiple electronic control switches displayed based on the parameter associated with the user.

[0017] Another apparatus is described. The apparatus may include means for providing an electronic user interface for interacting with an electronic device using a set of multiple electronic control switches displayed by the electronic user interface, where the electronic user interface can adjust a complexity level of a display of one or more of the set of multiple electronic control switches, means for monitoring a parameter associated with a user when the user engages the electronic user interface, and means for adjusting the complexity level of the set of multiple electronic control switches displayed based on the parameter associated with the user.

[0018] A non-transitory computer-readable medium storing code is described. The code may include instructions executable by one or more processors to provide an electronic user interface for interacting with an electronic device using a set of multiple electronic control switches displayed by the electronic user interface, where the electronic user interface can adjust a complexity level of a display of one or more of the set of multiple electronic control switches, monitor a parameter associated with a user when the user engages the electronic user interface, and adjust the complexity level of the set of multiple electronic control switches displayed based on the parameter associated with the user.

[0019] Another method of adapting a brain-computer interface to a user is described. The method may include providing an electronic user interface that includes a set of multiple electronic control switches and a navigation tool for guiding navigation among the set of multiple electronic control switches, determining a traversal level for at least one electronic control switch based on an amount of time for a user to navigate to the at least one electronic control switch using the navigation tool, determining a selection level for the at least oneAttorney Docket No.: SYNC-N-Z054-00-WOelectronic control switch based on a quantity of instances of a selection input by the user to select the at least one electronic control switch, and adjusting the electronic user interface to be associated with a complexity level that is based on the traversal level and the selection level.

[0020] An apparatus is described. The apparatus may include a processing system that includes processor circuitry and memory circuitry that stores code. The processing system may be configured to cause the apparatus to provide an electronic user interface that includes a set of multiple electronic control switches and a navigation tool for guiding navigation among the set of multiple electronic control switches, determine a traversal level for at least one electronic control switch based on an amount of time for a user to navigate to the at least one electronic control switch using the navigation tool, determine a selection level for the at least one electronic control switch based on a quantity of instances of a selection input by the user to select the at least one electronic control switch, and adjust the electronic user interface to be associated with a complexity level that is based on the traversal level and the selection level.

[0021] Another apparatus is described. The apparatus may include means for providing an electronic user interface that includes a set of multiple electronic control switches and a navigation tool for guiding navigation among the set of multiple electronic control switches, means for determining a traversal level for at least one electronic control switch based on an amount of time for a user to navigate to the at least one electronic control switch using the navigation tool, means for determining a selection level for the at least one electronic control switch based on a quantity of instances of a selection input by the user to select the at least one electronic control switch, and means for adjusting the electronic user interface to be associated with a complexity level that is based on the traversal level and the selection level.

[0022] A non-transitory computer-readable medium storing code is described. The code may include instructions executable by one or more processors to provide an electronic user interface that includes a set of multiple electronic control switches and a navigation tool for guiding navigation among the set of multiple electronic control switches, determine a traversal level for at least one electronic control switch based on an amount of time for a user to navigate to the at least one electronic control switch using the navigation tool, determine a selection level for the at least one electronic control switch based on a quantity of instances of a selection input by the user to select the at least one electronic control switch, and adjust the electronic user interface to be associated with a complexity level that is based on the traversal level and the selection level.

[0023] Another method of adapting a brain-computer interface to a user is described. The method may include providing an electronic user interface that includes a set of multiple electronic control switches selectable by a user, where the electronic user interface can adjust aAttorney Docket No.: SYNC-N-Z054-00-WOcomplexity level of a display of the set of multiple electronic control switches, monitoring the user while the user engages with the electronic user interface to determine an actual interaction rate for the user, and adjusting the complexity level based on a comparison of the actual interaction rate to an expected interaction rate associated with a current complexity level for the user.

[0024] An apparatus is described. The apparatus may include a processing system that includes processor circuitry and memory circuitry that stores code. The processing system may be configured to cause the apparatus to provide an electronic user interface that includes a set of multiple electronic control switches selectable by a user, where the electronic user interface can adjust a complexity level of a display of the set of multiple electronic control switches, monitor the user while the user engages with the electronic user interface to determine an actual interaction rate for the user, and adjust the complexity level based on a comparison of the actual interaction rate to an expected interaction rate associated with a current complexity level for the user.

[0025] Another apparatus is described. The apparatus may include means for providing an electronic user interface that includes a set of multiple electronic control switches selectable by a user, where the electronic user interface can adjust a complexity level of a display of the set of multiple electronic control switches, means for monitoring the user while the user engages with the electronic user interface to determine an actual interaction rate for the user, and means for adjusting the complexity level based on a comparison of the actual interaction rate to an expected interaction rate associated with a current complexity level for the user.

[0026] A non-transitory computer-readable medium storing code is described. The code may include instructions executable by one or more processors to provide an electronic user interface that includes a set of multiple electronic control switches selectable by a user, where the electronic user interface can adjust a complexity level of a display of the set of multiple electronic control switches, monitor the user while the user engages with the electronic user interface to determine an actual interaction rate for the user, and adjust the complexity level based on a comparison of the actual interaction rate to an expected interaction rate associated with a current complexity level for the user.

[0027] Another method of adapting a brain-computer interface to a user is described. The method may include providing a display on an electronic user interface that includes a base arrangement of electronic control switches and includes a control setting configured to enable an additive display mode, where the electronic user interface can selectively add an additional region or pane including alternative electronic control switches without changing the base arrangement when the additive display mode is enabled, monitoring user interaction with theAttorney Docket No.: SYNC-N-Z054-00-WObase arrangement while the additive display mode is enabled, determining that the base arrangement exceeds a capability of a user based on the user interaction with the base arrangement, and adding, to the display and in response to determining that the base arrangement exceeds the capability of the user, the additional region or pane including the alternative electronic control switches without changing the base arrangement.

[0028] An apparatus is described. The apparatus may include a processing system that includes processor circuitry and memory circuitry that stores code. The processing system may be configured to cause the apparatus to provide a display on an electronic user interface that includes a base arrangement of electronic control switches and includes a control setting configured to enable an additive display mode, where the electronic user interface can selectively add an additional region or pane including alternative electronic control switches without changing the base arrangement when the additive display mode is enabled, monitor user interaction with the base arrangement while the additive display mode is enabled, determine that the base arrangement exceeds a capability of a user based on the user interaction with the base arrangement, and add, to the display and in response to determining that the base arrangement exceeds the capability of the user, the additional region or pane including the alternative electronic control switches without changing the base arrangement.

[0029] Another apparatus is described. The apparatus may include means for providing a display on an electronic user interface that includes a base arrangement of electronic control switches and includes a control setting configured to enable an additive display mode, where the electronic user interface can selectively add an additional region or pane including alternative electronic control switches without changing the base arrangement when the additive display mode is enabled, means for monitoring user interaction with the base arrangement while the additive display mode is enabled, means for determining that the base arrangement exceeds a capability of a user based on the user interaction with the base arrangement, and means for adding, to the display and in response to determining that the base arrangement exceeds the capability of the user, the additional region or pane including the alternative electronic control switches without changing the base arrangement.

[0030] A non-transitory computer-readable medium storing code is described. The code may include instructions executable by one or more processors to provide a display on an electronic user interface that includes a base arrangement of electronic control switches and includes a control setting configured to enable an additive display mode, where the electronic user interface can selectively add an additional region or pane including alternative electronic control switches without changing the base arrangement when the additive display mode is enabled, monitor user interaction with the base arrangement while the additive display mode isAttorney Docket No.: SYNC-N-Z054-00-WOenabled, determine that the base arrangement exceeds a capability of a user based on the user interaction with the base arrangement, and add, to the display and in response to determining that the base arrangement exceeds the capability of the user, the additional region or pane including the alternative electronic control switches without changing the base arrangement.

[0031] Another method of adapting a brain-computer interface to a user is described. The method may include providing a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display among a set of multiple interface tiers including a highest interface tier, determining whether the user is able to interact with the electronic user interface at the highest interface tier across a threshold quantity of sessions, and generating a graduation indicator in response to determining that the user is able to interact with the electronic user interface at the highest interface tier across the threshold quantity of sessions, where the graduation indicator indicates a recommendation for the user to transition to a nonadapting user interface that operates without complexity adjustment based on an ability level of the user.

[0032] An apparatus is described. The apparatus may include a processing system that includes processor circuitry and memory circuitry that stores code. The processing system may be configured to cause the apparatus to provide a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display among a set of multiple interface tiers including a highest interface tier, determine whether the user is able to interact with the electronic user interface at the highest interface tier across a threshold quantity of sessions, and generate a graduation indicator in response to determining that the user is able to interact with the electronic user interface at the highest interface tier across the threshold quantity of sessions, where the graduation indicator indicates a recommendation for the user to transition to a non-adapting user interface that operates without complexity adjustment based on an ability level of the user.

[0033] Another apparatus is described. The apparatus may include means for providing a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display among a set of multiple interface tiers including a highest interface tier, means for determining whether the user is able to interact with the electronic user interface at the highest interface tierAttorney Docket No.: SYNC-N-Z054-00-WOacross a threshold quantity of sessions, and means for generating a graduation indicator in response to determining that the user is able to interact with the electronic user interface at the highest interface tier across the threshold quantity of sessions, where the graduation indicator indicates a recommendation for the user to transition to a non-adapting user interface that operates without complexity adjustment based on an ability level of the user.

[0034] A non-transitory computer-readable medium storing code is described. The code may include instructions executable by one or more processors to provide a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display among a set of multiple interface tiers including a highest interface tier, determine whether the user is able to interact with the electronic user interface at the highest interface tier across a threshold quantity of sessions, and generate a graduation indicator in response to determining that the user is able to interact with the electronic user interface at the highest interface tier across the threshold quantity of sessions, where the graduation indicator indicates a recommendation for the user to transition to a non-adapting user interface that operates without complexity adjustment based on an ability level of the user.

[0035] In some aspects, the present disclosure includes a method of adapting a braincomputer interface to a user. In some aspects, the method includes providing a display on an electronic user interface operative with the brain-computer interface, where the display includes a plurality of active electronic control switches selected from a plurality of electronic control switches, where each of the active electronic control switches is selectable using a neural activity of the user and where the active electronic control switches are configured to interact with an electronic device, where the electronic user interface is configured for increasing or decreasing a complexity level of the display by increasing or decreasing a navigation complexity for the user to navigate the plurality of active electronic control switches for selecting a desired active electronic control switches using the neural activity; providing the user with an electronic testing activity on the electronic user interface, where the user engages the electronic testing activity using the neural activity; monitoring the electronic testing activity during engagement by the user and adjusting the complexity level in response to monitoring a result of the electronic testing activity.

[0036] In some aspects, the present disclosure includes a method of adapting a braincomputer interface to a user, the method comprising: providing an electronic user interface of the brain-computer interface, where the electronic user interface is configured to interact with an electronic device using a plurality of electronic control switches and where each of theAttorney Docket No.: SYNC-N-Z054-00-WOplurality of electronic control switches is selectable using a neural activity of the user, where the electronic user interface is configured to increase or decrease a complexity level of a display of one or more of the plurality electronic control switches displayed by the user interface; monitoring the user while engaging the electronic user interface to determine an ability level of the user to interact with the electronic user interface using the neural activity; using the ability level to adjust the complexity level of the plurality of electronic control switches displayed by the electronic user interface.

[0037] In some aspects, the present disclosure includes a method of adapting a braincomputer interface to a user, the method comprising: providing an electronic user interface of the brain-computer interface, where the electronic user interface is configured to interact with an electronic device using a plurality of electronic control switches displayed by the electronic user interface and where each of plurality of electronic control switches is selectable using a neural activity of the user, where the brain-computer interface is configured to increase or decrease a complexity level of the plurality of electronic control switches displayed by the electronic user interface; monitoring a parameter associated with the user and adjusting the complexity level of the plurality of electronic control switches displayed by the electronic user interface in response to the parameter.

[0038] In some aspects, the present disclosure includes a method of adapting a braincomputer interface to a user, the method comprising: providing an electronic user interface of the brain-computer interface, where the electronic user interface is configured to interact with an electronic device using a plurality of electronic control switches and where each of the plurality of electronic control switches is selectable using a neural activity of the user, where the electronic user interface is configured to increase or decrease a complexity level of a display of one or more of the plurality electronic control switches displayed by the user interface; monitoring the user to determine a parameter associated with the user; and using the parameter to adjust the complexity level of the display of the plurality of electronic control switches.

[0039] In another aspect, the present disclosure includes a brain-computer interface system comprising: an electronic device; a controller; a neural interface device configured to detect a neural activity from a brain of a user and the transmitter / receiver component is configured to transmit an electronic signal representative of the neural activity of the user to the controller; and an electronic user interface in electrical communication with the controller, where the electronic user interface is configured to interact with the electronic device using a plurality of electronic control switches displayed by the electronic user interface and where each of plurality of electronic control switches is selectable using the neural activity of the user, whereAttorney Docket No.: SYNC-N-Z054-00-WOthe brain-computer interface is configured to increase or decrease a complexity level of the plurality of electronic control switches displayed by the electronic user interface; where the controller is configured to provide the user with an electronic testing activity on the electronic user interface, where the user engages the electronic activity using the neural activity; where the controller is configured to monitor the electronic testing activity during engagement by the user to establish an ability level of the user to interact with the electronic testing activity and use the ability level to adjust the complexity level of the display of the plurality of electronic control switches.

[0040] Details of one or more implementations of the subject matter described in this disclosure are set forth in the accompanying drawings and the description below. Other features, aspects, and advantages will become apparent from the description, the drawings and the claims. Note that the relative dimensions of the following figures may not be drawn to scale.BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The drawings shown and described are examples and non-limiting. Like reference numerals indicate identical or functionally equivalent features throughout.

[0042] FIG. 1 illustrates an individual using an exemplary BCI system with an adaptive user interface.

[0043] FIG. 2 illustrates a schematic of an electronic device configured to provide an adaptive user interface.

[0044] FIGs. 3A-3C illustrate exemplary user interface designs for a BCI system.

[0045] FIG. 4A illustrates a flow chart of an exemplary method for adjusting an adaptive user interface of a BCI system.

[0046] FIGs. 4B to 4E represent a basic example of changing a complexity of a user interface.

[0047] FIG. 4F represents an example of switches that can have a rank and / or level that can be used when adjusting a user interface for purposes of illustration of determining a complexity level of a user interface.

[0048] FIGs. 5A-5B illustrate an exemplary testing activity on a user interface of a BCI system.

[0049] FIGs. 6A-6B and 7A-7B illustrate an exemplary testing activity on a user interface of a BCI system.

[0050] FIG. 8 illustrates exemplary results of a testing activity performed on an adaptive use interface of a BCI system.Attorney Docket No.: SYNC-N-Z054-00-WO

[0051] FIG. 9 illustrates an exemplary testing activity on a user interface of a BCI system.

[0052] FIGs. 10 and 11 show block diagrams of example devices that support adaptive user interfaces for brain-computer interface systems.

[0053] FIGs. 12 -18 show example methods that support adaptive user interfaces for brain-computer interface systems.DETAILED DESCRIPTION

[0054] The present disclosure relates to adaptive user interfaces for BCI systems. To engage with a user interface of a BCI system, a user may engage in intentional neural activity by performing an affirmative action to generate neural activity that can be detected. For example, such intentional neural activity can include thinking a particular thought or engaging in neural activity related to a particular body movement or muscle activity. The BCI system monitors the user’s neural activity, and once the system identifies intentional neural activity, the system activates an electronic command previously associated with that intentional neural activity. The electronic command ultimately allows the user to interact with one or more electronic devices. In one example, a user interface operatively interfaces with the BCI system and includes one or more electronic control switches that can interact with an external device (e.g., a personal electronic device, a smartphone, a tablet, a mobility device, an electronically controlled wheelchair, a computer, an electronic prosthetic, etc.). Once the BCI system identifies an intentional neural activity, the system activates the appropriate electronic control switch to issue transmit the electronic command to the external device. For instance, a user can produce a thought associated with the activation of a muscle (e.g., movement of their left hand), and after the BCI system identifies this neural activity, the BCI issues a command to navigate on a menu of the user interface or may make a selection on the user interface to interact with an electronic device. The command produced by the BCI can trigger a click on a computer screen, a message for auditory output on a voice assistant, movement of a prosthetic hand, or any other command executable via the BCI system upon recognizing intentional neural activity as well as other neural activity of the user.

[0055] User interfaces for BCI systems include but are not limited to, electronic displays such as video displays, video projections, holographic displays, etc., where one or more electronic control switches are associated with one or more actions or tasks that allow the user to interface with an electronic device using the BCI system. For instance, user interfaces of a BCI system may include a display of electronic control switches for navigating menus of the user interface, interacting with electronic devices associated with the BCI system, and / or adjusting various parameters of the BCI system. Specific user interfaces may include subsets ofAttorney Docket No.: SYNC-N-Z054-00-WOelectronic control switches that correspond to specific tasks performed by a BCI system. For instance, specific user interfaces may be provided with electronic control switches for interacting with specific devices, engaging in digital or auditory communication, engaging in specific tasks, and performing other activities with a BCI system.

[0056] Given the wide range of potential users and use cases for BCI systems, user interfaces for BCI systems benefit from user- specific personalization and adjustment over time. This includes adjustment of the BCI interface to reduce the likelihood of user fatigue or user frustration in navigating the interface. For instance, novice users of BCI systems may prefer simpler user interfaces while they increase their experience with BCI systems, which may include user interfaces that are easier to navigate (e.g., user interfaces with fewer control switches, simplified layout of control switches, a different order of control switches, a greater spacing or lesser density of the control switches, differently colored or higher contrast control switches, different text associated with the control switches, or some other modification), modified user interface layouts, and different methods of engaging with the user interface using their neural activity. Higher proficiency users may desire more complex user interfaces that provide access to a greater quantity of control switches or provide more advanced means of navigating through menus of the user interface and issuing sophisticated commands via the BCI system. Additionally, the proficiency of an individual user can vary based on various factors, so different user interface designs may be desired at different points in time. For instance, a user may desire a simpler user interface when they are fatigued, at nighttime, at specific locations, or in specific use cases. Further, a user’s capacity to navigate user interfaces may increase over time (e.g., as they gain experience using a brain-computer interface system) or decrease over time (e.g., as they grow fatigued or a neurological condition progresses and prevents more advanced use of a brain-computer interface). Adaptive user interfaces can improve users’ ability to engage with BCI systems by providing personalized user interfaces that dynamically adjust according to various parameters. In additional cases, the use of an adaptive interface allows for dynamic personalized user interfaces without intervention by a caregiver.

[0057] In some examples, adaptive user interface systems may determine a particular users’ ability level and use this data to guide user interface design, e.g., by arranging electronic control switches in a desired pattern and / or by increasing or decreasing the level of complexity of electronic control switches on the user interface. In some cases, the ability level of BCI users is determined via electronic testing activities that the user can perform on the user interface. User proficiency may also be determined by monitoring the user while the user engages with the user interface during everyday use of the BCI system. Accordingly, adaptive user interfacesAttorney Docket No.: SYNC-N-Z054-00-WOmay track users’ ability levels and automatically adjust as a user grows more competent with BCI systems or as their ability level changes due to external factors, such as a medical event or the progression of a neurological condition.

[0058] Adaptive user interface design may also be guided by other data, such as physiological data associated with the user, data associated with the environment or location of the BCI user, the time of day, or an anticipated task the BCI user may engage in. For instance, a BCI system may recognize that the user is at home and may present an adapted user interface with control switches for accomplishing household tasks or interacting with electronic devices around the home. If the BCI system recognizes the user is at a different location (e.g., a hospital, a clinic, a workplace, a store, etc.) or engaged in a different activity, then the BCI system may adjust the user interface to include control switches suited to the BCI’s potential use in that situation. The time of day or night, when the user may generally be more tired, and physiological data may indicate that the user is struggling to use the user interface or would prefer a different user interface layout. The user interface may then adjust the complexity level, layout, or navigation method of the user interface accordingly.

[0059] Through automatic adjustments to user interfaces and the control switches thereon, adaptive user interfaces may better anticipate the needs of specific users throughout the lifespan of a BCI system. Adaptive user interfaces may also reduce the cost of in-person training programs that expect individuals to adjust user interface parameters of BCI systems. The reduction in in-person training programs can significantly reduce the costs and increase deployment of BCI systems, especially in the context of a multitude of BCI users. Accordingly, adaptive user interfaces may increase the level of autonomy of BCI system users and expand the potential users and use cases for BCI systems.

[0060] As used herein, the term “electronic testing activity” encompasses any activity, task, protocol, or mechanism by which the system evaluates, assesses, or monitors a user’s ability to interact with an electronic user interface. The terms and phrases “performance monitoring,” “pacing index determination,” “calibration session,” “evaluation stage,” “UI level assessment,” “UI level assessment mechanism,” “BCI literacy evaluation,” “BCI literacy assessment,” “assessment modality,” “intentional or dedicated assessment modality” (and other similar phrases such as a “specifically prompted, dedicated, or intentional test” or any other “dedicated assessment protocol”), “passive or continuous assessment modality” (and other similar phrases such as “passive continuous assessment,” “passive performance monitoring,” or “passive assessment modality”), and “determining the ability level” of a user, as used anywhere in this disclosure, may be examples of “electronic testing activity.” Any one or more of the specific types of tests described herein, such as “levels test,” “single switch scanner test,”Attorney Docket No.: SYNC-N-Z054-00-WO“multi-action scanner test,” “target word or phrase test,” “moving target test,” or “chase-a-target test,” also may be examples of “electronic testing activity.” Any implementation described in connection with one such term or phrase may be applicable to any other, and no distinction between these terms or phrases is intended unless explicitly stated.

[0061] An electronic testing activity may be intentional (such as dedicated) or passive. An intentional electronic testing activity is one in which the user is explicitly prompted to engage in one or more target selection tasks for the (dedicated) purpose of evaluating the user’s ability to interact with the electronic user interface, such as the levels tests described herein. A passive electronic testing activity, also referred to herein as passive performance monitoring or passive continuous assessment, is one in which the system evaluates the user’s ability to interact with the electronic user interface by observing the user’s interactions during ordinary, “non-testing” (in that the user is not performing a specifically prompted, dedicated, or intentional test, or any other dedicated assessment protocol) use of the electronic user interface. Both intentional and passive electronic testing activities may be examples of electronic testing activities as described herein, and any implementation described in connection with one may be applicable to the other unless explicitly stated otherwise. In some implementations, a user may perform an intentional electronic testing activity, and the system may (subsequently, periodically, continuously, or occasionally) perform a passive electronic testing activity. In some other implementations, the system may support one of intentional electronic testing activities or passive electronic testing activities.

[0062] As used herein, the term “complexity level” encompasses the overall difficulty, sophistication, or navigational burden of the electronic user interface as presented to the user at any given time. The terms and phrases “UI level,” “UI configuration,” “(dynamic) UI layout,” “interface level,” “interface tier,” “interface mode,” “interface configuration,” “interface complexity,” “layout,” “complexity setting,” “navigation complexity,” “difficulty level,” “scan timing,” “hierarchical depth,” “navigation burden,” and “ability-matched interface configuration,” as used anywhere in this disclosure, may be examples of “complexity level.” Any implementation described in connection with one such term or phrase may be applicable to any other, and no distinction between these terms or phrases is intended unless explicitly stated.

[0063] As used herein, the phrase “result of an electronic testing activity” encompasses any output, score, metric, or indicator derived from, based on, or generated by an electronic testing activity, performance monitoring session, or ability assessment. The terms and phrases “pacing index,” “BCI literacy score,” “UI level score,” “ability level,” “literacy score,” “numerical level score,” “error rate,” “accuracy,” “reproducibility,” “consistency score,”Attorney Docket No.: SYNC-N-Z054-00-WO“opportunity weight,” “scoring weight,” “selection strike rate,” “traversal level,” “selection level,” “response time,” “throughput,” “performance-implied level,” and any other numeric, quantitative, or qualitative score or metric derived from monitoring a user’s interaction with the electronic user interface, as used anywhere in this disclosure, may be examples of a “result of an electronic testing activity.” Any implementation described in connection with one such term or phrase may be equally applicable to any other, and no distinction between these terms or phrases is intended unless explicitly stated.

[0064] The various aspects of this disclosure (including exemplary testing activities, the pacing index mechanism, the UI level assessment mechanism, passive continuous assessment, and BCI literacy scoring) each describe implementation examples of a triggered, continuous, and / or automated evaluation of a user’s ability to interact with an electronic user interface, and the use of that evaluation to dynamically adjust the complexity of the interface to match the user’s current capabilities. Such various aspects may be implemented alone or in any combination with each other.

[0065] Exemplary BCI Systems

[0066] FIG. 1 is a representative illustration of a BCI 100 comprising a neural interface 101, a receiver transmitter unit 102, a lead 103 connecting the neural interface 101 to the receiver and transmitter unit 102, and a signal control unit 104. In this variation, the neural interface 101 is positioned within a brain 22 of an individual 20 where the BCI 100 operates with a user interface 200 operative with the BCI 100. While the illustrated example shows the user interface 200 on a separate device 202, in some variations, the user interface 200 can be considered as part of the BCI. In this example, neural interface 101 (which may be an implant) can be coupled to a receiver and transmitter unit 102 using a lead 103, where the receiver and transmitter unit 102 produces an electronic neural signal from the electrode device corresponding to brain signals from the brain 22 of the individual. The neural interface 101 may be coupled to the receiver and transmitter unit 102 via one or more leads 103. However, this communication can occur wirelessly.

[0067] FIG. 1 also shows the receiver and transmitter unit 102 having an ability to communicate with a signal control unit 104 that receives transmissions from the receiver and transmitter unit 102 and is configured to perform signal processing on the electronic neural signal to perform any number of functions for interaction with an external device 130 or a number of host devices. A host device can comprise any electronic device, such as a computer or tablet, including dedicated and may also include non-dedicated (proprietary and / or nonproprietary) applications. The host device can support secure and proprietary communication with the signal control unit 104 and can provide a user interface for the individual BCI user. InAttorney Docket No.: SYNC-N-Z054-00-WOsome variations, individuals use the host device to control a wide variety of applications, including an external electronic device 80 (e.g., a portable electronic device 82, a mobility assistance device 84, and / or a computer 86).

[0068] It is noted that the system shown in FIG. 1 is meant to illustrate the adaptive user interface that benefits any type of BCI, such as those that use various other implantable and non-implantable external devices.

[0069] In some BCI systems, the individual 20 generates neural activity that ultimately produces and engages the adaptive user interface 200 in order to interact with the one or more electronic devices 80. The signal can be an endogenous signal that originates within the individual, such as a signal associated with the individual’s brain activity, or an exogenous signal originating from an external device, such as a signal generated by an eye or body movement tracking camera.

[0070] In some aspects, the neural activity detected by the neural interface device may be decoded by processing raw electrical signals recorded from the brain of the user. The raw electrical signals may be filtered in one or more desired frequency bands using one or more frequency decomposition methods, such as a bandpass filter or a wavelet convolution. The desired frequency bands may include, for example, a delta frequency band (about 0.1 Hz to 3 Hz), a theta frequency band (about 4 Hz to 7 Hz), an alpha or mu frequency band (about 7 Hz to 12.5 Hz), a beta frequency band (about 14 Hz to 30 Hz), a gamma frequency band (about 30 Hz to 135 Hz), a sensorimotor rhythm (SMR) frequency band (about 12.5 Hz to 15.5 Hz), or any combination thereof, or more broadly any frequency band between 0.1 Hz and 32 kHz. Once filtered, voltage values of the filtered raw electrical signals may be converted into magnitude or power-related values for each of the desired frequency bands, expressed for example as V2 / Hz, pV2 / Hz, dB / Hz, z-scores, or normalized ratios relative to a baseline level of neural activity.

[0071] In some aspects, the decoder may identify transient oscillatory or pseudo-oscillatory bursts from the power-related values by applying one or more thresholds. A power threshold may be applied to the magnitude or power-related values for each desired frequency band, and a duration threshold may be applied to determine whether a detected signal event persists for a sufficient duration to constitute a burst. A transient oscillatory or pseudo-oscillatory burst may be identified when one or more of the magnitude or power-related values exceeds the power threshold and the duration of the signal event exceeds the duration threshold for a given frequency band. Such transient bursts may be characterized by being brief in duration (for example, between 1 ms and 100 ms) and by exhibiting power that exceeds a threshold level determined relative to a baseline level of neural activity and / or backgroundAttorney Docket No.: SYNC-N-Z054-00-WOnoise. These transient bursts differ from sustained increases in oscillatory power and from action potential spike events, and exhibit specific burst characteristics or features that differ across mental states or depending on the thoughts generated or conjured by the user. One or more of the power threshold and the duration threshold may be selected or optimized based on at least one training session conducted with the user, in which the user is prompted to generate or conjure a thought or evoke a change in mental state, and the thresholds are set to distinguish the transient oscillatory or pseudo-oscillatory bursts from background noise.

[0072] In some aspects, one or more burst features may be extracted from the transient oscillatory or pseudo-oscillatory bursts detected within a detection period, which may be between 1 ms and 100 ms in length. Burst features that may be extracted include, without limitation, a burst count, a burst rate, a burst band frequency or frequency distribution, an interburst interval length, a burst timing or timing pattern, an average burst duration, a burst waveform, an average power across bursts within a window of time, a maximum power of the bursts, a number of cycles, a peak frequency of the bursts, a frequency span, an oscillatory score, a burst synchronization or distance measure, the left and / or right slope of the transient bursts, and repeating sequences in time of transient bursts. The burst rate, in particular, may be calculated by dividing a burst count by the length of the detection period, where the burst count is calculated by summing all transient oscillatory or pseudo-oscillatory bursts detected across all electrodes, or a subset of electrodes, of the recording device within the detection period. A classification layer of the decoder may then predict the thought generated or conjured by the user or the change in mental state evoked by the user by applying at least one of a machine learning algorithm and a feature threshold to the one or more burst features extracted within the detection period. The machine learning algorithm may be a neural network, such as a recursive neural network or a long short-term memory (LSTM) network. The feature threshold may be a static threshold set in advance of use, or a dynamic threshold adjusted over time, and may require that the signal cross the threshold for a specific duration. An input command associated with the prediction may be transmitted to a device in order to control the device.

[0073] In some aspects, the decoder may be configured to adapt its decoding algorithm based on contextual data associated with the user, in a process referred to herein as contextualized decoding. Rather than applying a single fixed decoding algorithm at all times, the decoder may selectively apply at least one algorithm from multiple available decoding algorithms based on contextual input data generated by monitoring the user and the electronic devices with which the user is interacting. Such contextual data may include information regarding which electronic devices are presently connected to or actively engaged with the BCI system, what type of application or screen is currently in use, whether the user is attempting toAttorney Docket No.: SYNC-N-Z054-00-WOmove a cursor or enter text, environmental factors associated with the user such as ambient noise or temperature, physiological data associated with the user such as heart rate or fatigue level, and / or a history of prior output signals transmitted to one or more external electronic devices by the user. The selection among decoding algorithms based on this contextual data may result in, for example, reducing the latency of the output signal (for example, by selecting an asynchronous decoding algorithm that makes predictions on a quasi-continuous basis, such as one prediction every 100 ms), increasing the accuracy of the output signal (for example, by selecting a synchronous decoding algorithm that makes predictions on a longer timescale, such as 2 to 4 seconds, suited to higher-consequence application state changes such as sending an email), or producing the output signal as a continuous output signal (for example, when the user is moving a cursor) or as a discrete output signal (for example, when the user is selecting a button or link). In some aspects, the decoder may also be configured to switch between decoding algorithms that target different neural phenomena, such as oscillatory bursts for volitional, fast-acting selections suited to applications such as typing, or error-related potentials (ErrPs) for detecting when an erroneous action has been taken following an application state change.

[0074] Additional details regarding the detection and decoding of neural signals, and regarding the use of contextual data to adaptively select among decoding algorithms in a braincomputer interface system, are described in International Patent Application Publication No. WO 2023 / 240043, titled “Systems and Methods for Controlling a Device Based on Detection of Transient Oscillatory or Pseudo-Oscillatory Bursts,” and International Patent Application Publication No. WO 2025 / 096439, titled “Contextualized Decoding for Brain Computer Interface Systems,” the contents of each of which are incorporated herein by reference in their entireties.

[0075] User interfaces 200 for BCI systems may be viewed on an electronic display associated with a BCI system (e.g., a display included on the electronic system). However, user interfaces may also be displayed by other means (e.g., by projecting the user interface onto a surface in the environment or displaying the user interface using an external device, such as a computer, a smart phone, a tablet, or glasses). Further, any type of BCI system can be used in association with the adaptive user interfaces described herein. For example, additional variations of BCI systems can include electrodes positioned on an exterior of the individual, electrodes that are implanted directly into the brain through a skull of the individual, or any other electrode positioning configuration. Further, the methods and systems of the present disclosure are not limited to BCI systems. Rather, adaptable user interfaces can be employed in any electronic control system.Attorney Docket No.: SYNC-N-Z054-00-WO

[0076] FIG. 2 shows a schematic of an electronic device 202 configured to provide an adaptive user interface 200 as described herein. The exemplary adaptive user interface 200 can rely on a variety of components 50, such as controller 52, hardware 54, a memory 56, one or more adaptive user interface applications 58, and an optional network interface 66. The controller 52 can be in electrical communication with the adaptive user interface 200 and further in electrical communication with hardware 54 associated with a user, such as a neural interface device configured to detect neural activity from a brain of the user and / or transmitter and receiver components configured to transmit electrical signals representative of the neural activity to the controller 52. The components 50 can optionally include databases 60, 62 that are stored locally on the system and include individual-specific data and program data for adjusting the adaptive user interface 200. Additionally, or alternatively, the components 50 can use a network interface 66 to establish a network connection 70 to access one or more remote servers 72. The remote servers 72 may include additional databases 74, 76 with data used for operating the BCI system 50 and adjusting the adaptive BCI 100.

[0077] FIGs. 3A to 3C show variations of user interfaces for use with a BCI where the user interface is configured to increase or decrease a complexity level of the display by increasing or decreasing a navigation complexity for the user to navigate the plurality of active electronic control switches for selecting a desired active electronic control switches using the neural activity.

[0078] Exemplary user interfaces for BCI systems may include one or more electronic control switches selectable on an electronic display using the neural activity of a user. In some examples, an electronic control switch may be associated with a particular form of neural activity, such as a particular thought or movement (or attempted movement) of a particular part of the body. A user of the BCI system may then select a particular control switch by engaging in the form of neural activity that has been previously associated with the control switch. For instance, a first control switch may be associated with neural activity associated with the movement of the user’s left hand, while a second control switch may be associated with neural activity associated with the movement of the user’s right hand, etc. The user may select the first control switch by engaging in neural activity associated with movement of their left hand, and the second control switch may be selected by engaging in neural activity associated with movement of their right leg, etc. Selection of a control switch may cause the BCI system to transmit a command to one or more electronic devices associated with the BCI system to cause the electronic device(s) to perform an action.

[0079] In some examples, a user interface may include one or more active control switches and one or more inactive control switches. An active control switch may be a control switchAttorney Docket No.: SYNC-N-Z054-00-WOthat is configured to interact with an electronic device, e.g., by causing a command to be sent to the electronic device to perform an action. An inactive control switch may be presented on the user interface and may not interact with an electronic device or may be non-selectable by the user. An example of an inactive control switch is an informational control switch that may provide information to the user on the user interface but may be non-selectable via the user’s neural activity.

[0080] Control switches may be arranged on the user interface in various patterns (e.g., grid patterns), in nested user interface menus, or in any other desired format that makes them navigable to users of BCI systems. Each control switch may include associated text, color, and other indicators that make them visually distinguishable to the user of the BCI system.Navigation between control switches on a user interface (and / or various menus of the user interface) may be controlled via the neural activity of the user. For instance, various control switches may be provided for navigating between user interfaces menus and individual control switches displayed on the user interface.

[0081] In some examples, navigation between control switches on a user interface may be facilitated by one or more navigation tools, such as an indicator, a cursor, or some other visual aid. In such examples, a user may select a desired control switch by engaging in neural activity while the navigation tool is in a position corresponding to the position of a desired control switch. In some examples, movement of the navigation tool within the user interface is controlled via the neural activity of the user. For instance, a user may engage in neural activity to cause the navigation tool to move from a first control switch to a second control switch or from a first subset (e.g., column / row) of control switches to a second subset (e.g., column / row) of control switches. In other examples, movement of the navigation tool may proceed along a predefined path between various control switches on the user interface, and the user may engage in neural activity while the navigation tool is in a position corresponding to a desired control switch to select the control switch. Various examples of user interfaces for braincomputer interface systems are described in U.S. Patent Application No. 17 / 818,227, incorporated herein by reference. However, this disclosure is not limited to the particular user interface designs or the methods of navigating user interfaces shown and described herein.

[0082] FIGs. 3A illustrates arrangements of electronic control switches (e.g., 310, 312, 314, 316) on exemplary user interface 300 of a BCI system, where the user interface shows a “Pain Scale” screen to allow a user to communicate a level of pain. As shown in FIG. 3A, the user interface 300 can include any quantity of control switches. In this variation, the control switches are arranged in a 3x4 array including a control switch 310 for communicating “Mild” pain, a control switch 312 for communicating “Distressing” pain, a control switch 314 forAttorney Docket No.: SYNC-N-Z054-00-WOcommunicating “Unbearable” pain, and a control switch 316 for navigating “Back” to a different menu of the user interface. The control switches may be arranged on the user interface 300 in any pattern aside from a 3x4 grid.

[0083] In the user interfaces 300 shown in FIGs. 3A-3C, selection of various control switches is facilitated by an indicator 302 (such as an effector). As shown in FIG. 3A, the indicator 302 travels along a predefined path indicated by the dotted line, with the arrows indicating the indicator’s direction of movement. The user selects a desired control switch by waiting for the indicator 302 to move along the path. When the indicator 302 passes over the desired switch, the user produces neural activity to trigger the BCI system to select that electronic control switch.

[0084] In this particular example, the indicator 302 can begin movement on any portion of the array of switches, e.g., starting on the “Back” control switch 316, and proceeds to advance rightward across the first row of control switches until it arrives at the “Mild” pain switch 310. The indicator 302 then moves to the second row and advances across the second row of control switches rightward across the second row of control switches until it reaches the “Distressing” control switch 312. The indicator 302 then advances to the third row of control switches, beginning at the leftmost “Unmanageable” control switch and moving rightward across the third row of control switches until it reaches the “Unbearable” control switch 314. The indicator 302 then returns to the top left “Back” control switch 316 and repeats the same predefined movement path.

[0085] FIG. 3A is provided as an example of a relatively more difficult navigation interface when compared to the examples shown in FIGs. 3B and 3C, as discussed below. The user interface 300 of FIG. 3A may expect a user to navigate a 3x4 array, which may involve the user maintaining concentration until the indicator 302 reaches a desired electronic switch. This means that the user is tasked to avoid triggering a selection of an electronic switch unintentionally (i.e., by not generating the neural activity). In addition, a user, either a new user or a fatigued user, could find the number of choices excessive to the point that the user experiences difficulty navigating a relative complex user interface, which adds to fatigue and frustration. It was found that this could ultimately discourage users from fully using or adopting a BCI systems. Conversely, a more sophisticated user who easily navigates the user interface of FIG. 3A can find that the user interface is insufficiently sophisticated and lacks options for quickly engaging with BCI systems.

[0086] Accordingly, as described herein, the BCI system (optionally including the components of the user interface) can assess the individual user to determine whether to increase or decrease a complexity of the user interface.Attorney Docket No.: SYNC-N-Z054-00-WO

[0087] FIGs. 3B and 3C illustrate an example where the pain scale user interface is reduced in complexity. If the system determines (either through testing of the individual, monitoring of the individual, monitoring of the individual’s environment, and / or a combination) that a complexity of the user interface should be reduced, the system can present a user interface the individual such as the ones shown in FIG. 3B and 3C, which are less complex than the interface of FIG. 3 A and easier to navigate. As shown in FIG. 3B, the interface 300 comprises a range of “0 - No Pain” to “10 - Unbearable” using three electronic control switches 318, 320, 322. Upon selecting switch 320 with the indicator 302, the user interface 300 of FIG. 3C appears and provides four electronic switches 324, 326, 328, and 330, where the individual can select the appropriate switch using the indicator 302. As discussed below, the system can assess the user to determine a level of complexity that the user is capable of handling for a user interface and adjust the user interface accordingly.

[0088] In some examples, a user of the BCI system can also manually adjust various parameters of the user interface, such as the number of control switches on the user interface, the presence of text or color associated with the control switches, the layout of the control switches, the method of navigating through the control switches, or any other desired parameter of a user interface, where such parameters of the user interface may individually or collectively determine a complexity level. In some examples, a user may manually adjust the complexity of the user interface, e.g., by using control switches to select between various user interface layouts (e.g., various complexity levels). For instance, a menu within the user interface may allow a user to toggle between user interfaces of varying complexity levels to select a user interface of a desired complexity level. In some examples, a user interface for a BCI system may permit a user to navigate between various predefined menus associated with the user interface. For example, a user may select a control switch to navigate to a user interface menu that includes a subset of control switches associated with a particular task, e.g., a user interface for auditory communication via a vocal assistant, a user interface for typing, a user interface for controlling a particular electronic device, etc. In a particular example, a menu within the user interface may allow a user to select between keyboard layouts of varying complexity (e.g., a QWERTY keyboard, an ABC basic keyboard, an ABC tiered keyboard, or a vowel-based keyboard) for display on the user interface. Each keyboard layout may be an example of or otherwise associated with a respective complexity level.

[0089] In some aspects, a BCI system may include one or more adaptive user interfaces that adjust various parameters of the user interface in accordance with data associated with the user. FIG. 4A shows an exemplary method for adapting a user interface of a BCI system to a user. First, the BCI system may provide a user interface to the user that includes a plurality ofAttorney Docket No.: SYNC-N-Z054-00-WOcontrol switches that the user interacts with using their neural activity. The BCI system then monitors various parameters to generate data about the user. For instance, the BCI system may monitor the user while engaging with the user interface to determine the user’s ability level (e.g., the user’s response time, their accuracy in control switch selection, or the reproducibility of their neural activity, each of which may be an example of a result of one or more electronic testing activities), monitor the user to determine various parameters associated with the user (e.g., physiological parameters of the user, such as heart rate, body temperature, blood pressure, breathing rate, pupil dilation, etc.), or monitor additional parameters associated with the user (e.g., the user’s location). Optionally, the BCI system may present an electronic testing activity, and the user is monitored while engaging with the electronic testing activity to generate data used for adaptive user interface design. The BCI system then uses this data to determine an adjusted user interface for the BCI system. The BCI system then provides the adjusted user interface to the user. In a particular example, a BCI system may automatically present a medical user interface with healthcare-related control switches when data indicates that the user is at a hospital or medical clinic. If data indicates that the user is growing fatigued during use of the BCI system, the BCI system may lower the complexity level of the user interface. In another example, the BCI system may determine that a user selects a particular control switch with greater frequency, and may adjust the user interface to locate that control switch in a more convenient location on the user interface. The complexity level of the user interface generally equates to a difficulty level of navigating the user interface by an individual. Complexity can include factors, including but not limited to the number of choices of electronic control switches, the size of the button associated with a switch, the location of the switch on the user interface, the speed at which the effector moves over various switches, etc.

[0090] FIGs. 4B to 4E represent a basic example of changing a complexity of a user interface. FIG. 4B shows an example of a user control interface 250 having eight electronic switches 260 (not including a “back” switch”). As noted herein, the user navigates the interface 250 using one or more of the selection methods discussed elsewhere herein. FIG. 4C illustrates an electronic interface 252 having five electronic switches to provide an interface 252 that is less complex than the interface 250 of FIG. 4B. FIG. 4D shows a user interface 254 with four electronic switches 260 and FIG. 4E shows a user interface 256 with two electronic switches 260. For purposes of illustration, the complexity level of the user interfaces 250, 252, 254 and 256 reduces in complexity by reducing the number of available switches 260. It is noted that reducing the number of electronic switches 260 displayed on an interface is one means of adjusting complexity of the interface. FIG. 4F represents an example of switches 260 that can have a rank and / or level that can be used when adjusting a user interface for purposes ofAttorney Docket No.: SYNC-N-Z054-00-WOillustration of determining a complexity level of a user interface. The rank or level of each switch can be set by the user, a caregiver, or the system. In the present example, the level of each switch is identified or categorized such that a user interface having the lowest level of complexity (e.g., user interface 256 in FIG. 4E) will use the switches 260 having a “1” level. Alternatively, or in combination, a user, caregiver, or the system can rank switches in order of importance, such that those switches will appear at lower levels of complexity. In such a case, the user, caregiver, or the system can identify the switches 260 that should appear when the number of switches is reduced.

[0091] Various parameters can be adjusted in an adaptive user interface. For instance, an adaptive user interface may adjust a number of control switches on the user interface, a type or subset of control switches on the user interface, a layout of the control switches on the user interface, an order of the control switches on the user interface, a spacing or density of the electronic control switches on the user interface, a color associated with the control switches, text associated with the control switches, a speed of the selection cursor / indicator / effector and / or another criteria about the user interface and control switches thereon. Various aspects of the hardware may also be changed, such as a level of brightness of a screen on which the user interface is provided or the algorithm used to process signals from a user’s neural activity during engagement with the user interface to determine the selection of a control switch (e.g., to allow the user to select a control switch with more precise or less precise signals representative of their neural activity).

[0092] Adaptive user interfaces may also change various ways that a user navigates between control switches or menus on the user interface. For instance, an adaptive user interface may adjust a number of menus on the user interface, a method of interacting with a navigation tool of the user interface, a path of an indicator used to select between control switches on the user interface (e.g., to cause the indicator to initiate movement on a particular control switch that is more frequently selected by the user), a speed of an indicator, a response time for selecting a desired control switch, etc. In some examples, an adaptive user interface may modify the type of neural activity associated with selection of particular control switches. For instance, a user may repeatedly fail to select a control switch that is activated via neural activity associated with the movement of their left hand. The adaptive user interface may adjust the user interface by replacing that type of neural activity with a different form of neural activity, or by providing a user interface that limits the requirement to engage in neural activity associated with movement of their left hand.

[0093] To facilitate the generation of adaptive user interfaces, user interface designs may be scored based on quantitative metrics. For example, a complexity level of a user interface mayAttorney Docket No.: SYNC-N-Z054-00-WObe determined based on a number of control switches on the user interface, a layout of the switches, a spacing or density between the switches, a number of menus on the user interface, an error rate (e.g., a result of an electronic testing activity) of a user when using the user interface, or some other metric. Additionally, or alternatively, a complexity level of a particular control switch may be determined based on quantitative metrics. For example, the complexity level of an electronic control switch may be determined based on an amount of time required to navigate to a control switch (i.e., a “traversal level,” which may be an example of a result of an electronic testing activity), which may correlate to the amount of time required for a navigation tool to navigate to a desired control switch. In some examples, the complexity level of an electronic control switch is determined based on the instances of neural activity required to select a control switch (i.e., a “selection level,” which may be an example of a result of an electronic testing activity). In some aspects, a weight may be assigned to various forms of neural activity used to select control switches on the user interface. The weighting of the selection levels may be based on a difficulty in engaging in the various forms of neural activity (e.g., because some users may have more difficulty in engaging in a particular type of neural activity, such as a particular thought, while other users may find that form of neural activity easier to engage in). In some examples, the weighing of each form of neural activity is userspecific, e.g., based on data about the user’s own competency in engaging in the forms of neural activity.

[0094] The overall complexity level of a control switch may be determined by summing or otherwise combining the traversal level and selection level (results of one or more electronic testing activities) of the control switch. In some examples, the overall complexity level of a control switch may be based on weighted values of the traversal level and selection level of the control switch. For instance, some users may have more difficulty waiting for the navigation tool to arrive at the control switch (resulting in a relatively increased weighting of the traversal level) while some users may have more difficulty selecting a control switch using their neural activity (resulting in a relatively increased weighting of the selection level).

[0095] In some examples, a complexity level of a user interface may be quantified based on a complexity level of one or more electronic control switches included on the user interface. For example, a complexity level of a user interface, including multiple control switches, may be determined based on the complexity level of the most complex control switch (i.e., such that the user interface does not include any electronic control switches that exceed a maximum complexity level). However, in other examples, the complexity level of a user interface may be based on an average or weighted average of the complexity level of the control switches (or a subset of the control switches) on the user interface. Yet further, the complexity level of a userAttorney Docket No.: SYNC-N-Z054-00-WOinterface may be determined based on other metrics, such as a number of control switches, a layout or density of the control switches, a number of menus in the user interface, a speed of the navigation tool, etc. However, this disclosure is not limited to a particular calculation for determining a complexity level of a particular electronic control switch or user interface or a particular way of quantifying various user interface designs.

[0096] User Testing for Adaptive User Interface Design

[0097] In variations of the system the users of a B CI system perform electronic testing activities on the user interface to determine quantitative metrics about the user. A user may be monitored during engagement with an electronic testing activity to establish, e.g., an ability level (e.g., a result of an electronic testing activity) of the user in navigating various user interfaces and selecting various control switches on a user interface. The user’s ability level (e.g., the result of the electronic testing activity) can then be used to dynamically adjust various parameters on an adaptive user interface. Such testing may provide a means of determining a quantitative metric associated with the user’s ability level (e.g., the result of the electronic testing activity) for guiding user interfaces provided by an adaptive user interface.

[0098] During a testing activity provided by the BCI system, the user may be monitored while engaging with the user interface to determine various parameters about the user. For instance, the user’s response time in selecting a desired control switch, the user’s accuracy in selecting the desired control switch instead of a non-desired control switch, or the reproducibility of the user’s selection (e.g., whether the user may repeatedly select a desired control switch or repeatedly engage in a particular form of neural activity to select a desired control switch), each of which may be an example of a result of the electronic testing activity. Such parameters may also be monitored during the user’s non-testing use of the BCI system. Additional parameters may also be monitored during a testing activity or during non-testing use of the BCI system to further quantify the user’s ability to engage with user interfaces and to facilitate the design of adaptive user interfaces.

[0099] In some aspects, a testing activity may occur when a user is prompted (e.g., when initiating setup of the BCI system or at the end of a default switch pipeline in which the user associates a neural signal with one or more commands to be issued by the BCI). In some examples, a user may be prompted to engage in a testing activity on a particular schedule or in response to certain circumstances. For instance, a user may be prompted to test when the braincomputer interface system determines that the user is making a great number (more than a threshold quantity) of errors (i.e., indicating that a simplified user interface may be desired), or that the user is making a fewer number of errors (i.e., indicating that the user is capable of navigating a more complex user interface with enhanced capabilities). In some examples, AlAttorney Docket No.: SYNC-N-Z054-00-WOmay be used to determine when the user is prompted to engage in a testing activity. For instance, an Al model may determine that the user is making an unusually higher number of errors when engaging a user interface and may determine that the user interface is unsuitable for that user. In other aspects, a user may engage in testing on their own volition, for example, by selecting a command switch on the user interface to initiate the testing activity.

[0100] In some aspects, an Al model used to determine when to prompt a testing activity may receive, as inputs, one or more of a rolling error rate associated with the user’s selection of electronic control switches during non-testing use, a response time for selection of electronic control switches, a pacing index, a traversal level or selection level associated with recent user interactions, physiological data associated with the user, a time of day, a session duration, or a history of prior testing activity results. The Al model may process these inputs using a trained classification or regression model (such as a neural network, a decision tree, a support vector machine, or any other supervised or unsupervised learning model trained on data from one or more BCI users) to output a recommendation as to whether a testing activity is to be initiated, and optionally to recommend a starting complexity level for the testing activity. In some aspects, the Al model may be trained on historical data associating patterns of user interaction performance with subsequent testing outcomes, such that the model leams to identify interaction patterns that predict that a reassessment may be suitable (e.g., provide a greater user experience for the user). In some aspects, the Al model may be implemented as a rule-based system that applies predefined thresholds to the input metrics, rather than a learned model, or as a hybrid system that combines learned components with rule-based component.

[0101] Example 1: Levels Test

[0102] FIGs. 5A-5B, 6A-6B, 7A-7B, and 8 show exemplary testing activities or “levels tests,” which may be examples of electronic testing activities. During a levels test, the user may be presented with one or more user interfaces and asked to engage with the user interfaces to determine their competency (e.g., their “ability level”) in interacting with the user interface. Through iterative testing, the levels test may determine quantitative data about the user’s engagement with the user interface and may update the user interface accordingly.

[0103] In some examples, the levels test may present the same user interface to the user and the user may be prompted to select a series of electronic control switches (“targets”) of varying complexity until an ability level (e.g., a result of an electronic testing activity) of the user is determined. In an initial trial of a levels test (e.g., an electronic testing activity), the user may be prompted to select a first target having a first complexity level on the user interface. If the user successfully selects the first target prompted by the test, then the testing activity may prompt a user to select a second target that has a higher complexity level than the previousAttorney Docket No.: SYNC-N-Z054-00-WOtarget. If the user fails to select the first target, then the testing activity may prompt the user to select a second target that has a lower difficulty level (e.g., a lower complexity level) than the first target. Testing may progress through a series of levels that change in difficulty according to a user’s performance in a previous level. Through iterative testing, the testing activity will arrive at the user’s ability level for engaging with user interfaces. The ability level of the user may correspond to the complexity level of the highest complexity target that the user can reliably select with less than a predefined error rate during the levels test.

[0104] In some aspects, Al may be used during a testing activity on an adaptive user interface. For instance, Al may be used to determine which targets to prompt a user to select during a testing activity. Additionally, or alternatively, Al may be used to generate user interfaces presented to the user in various testing activities. The Al model may use as inputs the user’s past success in selecting targets during the testing activity, the traversal level and the selection level of previous targets, the ability level of the user, the complexity level of previous targets and / or user interfaces, the error rate of the user when selecting targets, and other data about the user, such as the user’s error rate when selecting control switches during non-testing use of the user interface. The Al may then generate tailored testing activities that facilitate rapid and accurate determination of the user’s ability level.

[0105] Adapted user interfaces may then be presented to the user based on data generating during the testing activity. For instance, if levels testing (or any other electronic testing activity) indicates that a user has an ability level of “8”, user interfaces can be provided to the user that have a complexity level of “8” (or that have a complexity level not exceeding “8”). In some examples, the levels test may also determine a maximum traversal level and a maximum selection level of targets selectable by a specific user. Adaptive user interfaces may then be presented with control switches consistent with the maximum selection level and a traversal level selectable by the user. For instance, some users may be more capable of selecting control switches using neural activity but may have less capacity to wait as the indicator moves between the control switches. For such a user, an adapted user interface may minimize the traversal level of control switches on the user interface. Other users may be more capable of waiting as an indicator moves between control switches and may have less capacity to use their neural activity to select a control switch. For such a user, a suitable user interface may use fewer instances of neural activity for interface navigation and selection of control switches.

[0106] Example la: Single Switch Scanner Test

[0107] In one variation of a level test a user engages in a testing activity (e.g., an electronic testing activity) that includes a plurality of control switches selectable by one or more instances of the same form of neural activity. Such a test may be referred to as a single switch scannerAttorney Docket No.: SYNC-N-Z054-00-WOtest (e.g., an electronic testing activity). FIG. As shown in FIGs. 5A-5B, during engagement with the test, the user may be presented with a user interface having a number of control switches 260 arranged in a pattern (e.g., a 7x10 grid pattern). An indicator moves between the control switches along a predefined path (or in any other manner), and the user is prompted to select a target control switch 270 by engaging in neural activity while the indicator is in a position corresponding to the target.

[0108] As shown in FIG. 5A, the single switch scanner test prompts a user to select a target switch 270 of a particular complexity level, for instance, the center control switch having a complexity level of, e.g., “12”. FIG. 5B shows a successful selection of the center control switch target. Upon succeeding to select the target, the single switch scanner test will prompt a user to select a target with an increased complexity level (e.g., the bottom-right control switch having a difficulty score of, e.g., “20”). If the user succeeds in selecting the level “20” target, the single switch scanner test may determine that the ability level of the user is between “12” and “20”. The single switch scanner test will repeat this process by iteratively prompting the user to select targets of varying complexity levels based on the success of the user in selecting the previous target. This process will repeat until the single switch scanner test determines the highest complexity level control switch that the user can reliably select. The scores described herein are for exemplary purposes only.

[0109] The user interface designs shown in FIGs. 6A-6B and 7A-7B may also be implemented on a user interface of a BCI system and / or used during a levels test (e.g., an electronic testing activity). FIGs. 6A-6B and 7A-7B, an indicator 304 is used to guide a user to select a particular row or column of control switches to then select a control switch in that particular row or column. In these exemplary user interfaces, the indicator is represented by a visually distinct bar that moves across the control switches 260 along a predetermined path. For instance, as shown in FIG. 6A, the indicator may begin movement at the top-left control switch on the user interface and may advance across the first row of control switches. A user then selects a desired control switch by engaging in neural activity while the terminal end of the indicator 304 overlaps with the desired control switch 270 (or target). For instance, a user engaging in neural activity while the indicator is in the position shown in FIG. 6B may cause the selection of the target control switch shown in the exemplary levels test (as shown by the hatched control switch 270, such as a hatched target).

[0110] In some examples, a user may advance the indicator between rows or columns of control switches on the user interface by engaging in neural activity to cause the indicator to move between the rows or columns (e.g., to move from the first row to the second row or from the first column to the second column). FIGs. 7A-7B show the movement of a similar indicatorAttorney Docket No.: SYNC-N-Z054-00-WOrepresented by a visually distinct bar that moves across control switches 260 on the user interface. As shown in FIG. 7A, the indicator 304 initially advances across the first control switch 260 of the first row of control switches 260. If the user engages in neural activity while the indicator is moving across the first control switch in the first row, the indicator will continue moving across the first row of control switches, i.e., across the second, third, fourth, and further control switches in the first row. If the user does not engage in neural activity while the indicator is moving across the first control switch in the first row, the indicator will advance to the second row of control switches 260, as shown by lines 306, and begin moving across the first control switch in the second row. If the user engages in neural activity while the indicator is moving across the first control switch in the second row, the indicator will continue moving across the second row of control switches. If the user does not engage in neural activity while the indicator is moving across the first control switch in the second row, the indicator will advance to the third row of control switches.

[0111] As shown in FIG. 7B, a user may select the target control switch in the center of the user interface by foregoing neural activity during advancement of the indicator across the first control switch in the respective first, second, and third rows of control switches. The user may then engage in neural activity while the indicator is overlapping the first control switch in the fourth row of control switches to cause the indicator to continue to advance across the fourth row of control switches. The user may then select the target control switch by waiting for the indicator to advance across the fourth row of control switches until the terminal end of the indicator overlaps with the fifth control switch in the fourth row.

[0112] Such a navigation tool may allow a user to advance between rows (and / or columns) of control switches without requiring the user to wait for the indicator to advance across the entirety of a previous row (or column) of control switches. Similar navigation methods may be used for selection of columns of control switches, or for selecting between other patterns of control switches in a user interface. However, the examples shown in FIGs. 5A-5B, 6A-6B, and 7A-7B (as well as FIGs. 3A-3C described previously) are non-limiting. An indicator may move between rows, columns, or other subsets of the control switches in any number of ways without departing from the present disclosure.

[0113] FIG. 8 is an illustration of two scoreboards representing the outcome of a single switch scanner test. Scoreboard 150 in FIG. 8 shows that the user was prompted to select a target that is the central control switch in the user interface (the “R5C5” control switch, in the fifth row and fifth column of the grid of control switches). As shown in scoreboard 150, the user failed to select the first target control switch, and the single switch scanner test determines that the user’s ability level may be a “0”. Additional trials of the level test may prompt the userAttorney Docket No.: SYNC-N-Z054-00-WOto select targets of a lesser complexity level than the first target, allowing the user to advance their ability level above the level “0”.

[0114] Scoreboard 152 in FIG. 8 shows that the user was initially prompted to select a target in the first row and first column of the grid of control switches (the “R1C1” target). The user succeeded in selecting the target, and the levels test determined that the user’s ability level may be a “2”. The levels test continued by prompting the user to select a target in the second row and sixth column of the grid of control switches. The user succeeded in selecting the target control switch, and the levels test determined that the user’s ability level may be an “8”. The level’s test continued by prompting the user to select a target in the third row and third column of control switches and the user once again succeeded, causing the levels test to determine the user’s ability level may be a “10”. The levels test then prompted the user to select a control switch in the seventh row and third column of the grid of control switches. The user failed to select the target in the fifth trial, causing the levels test to determine that the user’s ability level is likely a “10”, which may correspond to the highest complexity level target the user can reliably select. Thus, the testing activity may indicate that an appropriate user interface for that user includes control switches having a complexity level not exceeding level “10”. An adapted user interface may then be generated that includes control switches not exceeding a complexity level of “10”.

[0115] Example lb: Multi-Action Scanner Test

[0116] In some aspects of the disclosure, a user may be presented with a testing activity (e.g., an electronic testing activity) that includes a plurality of control switches, each control switch selectable by one or more instances of different forms of neural activity. For instance, various targets may be presented to the user that require the user to engage in one or more of a first form of neural activity (e.g., neural activity associated with the movement of their left arm), a second form of neural activity (e.g., neural activity associated with movement of their right arm), and a third form of neural activity (e.g., neural activity associated with nodding their head). Such a test may be referred to as a multi-action scanner test (e.g., an electronic testing activity). An exemplary multi-switch scanner test is shown in FIG. 9.

[0117] In exemplary user interfaces requiring different forms of neural activity for target selection, a user may select a desired row, column, or subset of the switches by engaging in a particular form of neural activity associated with that row, column, or subset of switches. The exemplary multi-switch scanner test shown in FIG. 9 requires three instances of neural activity to select control switches on the user interface. The user interface shown in FIG. 9 includes 3x3 arrays nested within a larger 3x3 array, wherein a user selects various columns and rows within the arrays by engaging in neural activity corresponding to the first, second, and thirdAttorney Docket No.: SYNC-N-Z054-00-WOrows / columns of the arrays. Thus, to access the target control, switch “X” shown in the array of FIG. 9, a user would engage in a third form of neural activity to select the third row of the larger 3x3 array and then would engage in a second form of neural activity to select the second column of the larger 3x3 array. The user may then engage in a first form of neural activity two times to select the first row and the first column within the smaller nested 3x3 array.

[0118] Such a test may be suited to testing a user’s ability to engage in various different forms of neural activity for selection of a control switch. In some aspects, a weight may be assigned to the various forms of neural activity required during a multi-switch scanner test. Accordingly, each control switch in the multi-switch scanner test may be assigned a complexity level based on a weighted selection level. The weighting of the selection levels may be based on the user’s ability level in engaging in different forms of neural activity (e.g., the three forms of neural activity previously described). In some examples, the weighing of each form of neural activity is user-specific, e.g., based on data about the user’s own competency in engaging in each form of neural activity.

[0119] Data from such a multi-switch scanner test may be used to design user interfaces that are weighed toward a particular form of neural activity that is easiest for the user. For instance, a user may be more adept at selecting control switches using, e.g., a though neural activity associated with movement of their hands. Accordingly, a user interface may be designed that includes control switches requiring increased instances of that form of neural activity.

[0120] Other Data for Adaptive User Interface Design

[0121] In addition to testing-based data, user interfaces for BCI systems may also be adapted according to other data, such as data about a user’s past success using user interfaces of the BCI system (e.g., error rate data from the use of previous user interfaces), other data associated with the user (e.g., physiological data), data associated with the environment (e.g., geolocation data or weather data), or other data associated with context of use of the BCI system (e.g., the time of day or past use history of the BCI). Such data may be used to intelligently present an adapted user interface that is particularly suited to the user, user case, and environment of use of the BCI system without requiring the user to engage in a specific testing protocol.

[0122] In some aspects, a user interface may be adapted based on data associated with a user’s past use or non-testing use of a BCI system. For instance, the BCI system may initially present a default user interface to the user upon setup of the BCI system. The BCI system may subsequently monitor the user and collect data regarding the user’s interaction with the user interface, such as data relating to the user’s response time for control switch selection, theAttorney Docket No.: SYNC-N-Z054-00-WOaccuracy of their control switch selection, the reproducibility of their neural activity, etc., each of which may be an example of a result of an electronic testing activity. If the user’s interactions with the default user interface indicate that the user is having difficulty selecting control switches on the interface, the BCI system may determine that the user would benefit from a simplified user interface. The BCI system may then adjust the default user interface and present a new user interface having a complexity level corresponding to the user’s ability level. As described herein, various parameters may be associated with user interfaces (e.g., complexity level, number, layout, and spacing of control switches, navigation method between control switches, speed of a navigation tool, required response time, number and format of menus within the user interface, etc.) and particular control switches on the user interface (e.g., complexity level, traversal level, selection level, form of neural activity for selection, etc.). In such examples, the BCI system may collect data about such parameters by monitoring the user while the user engages with user interfaces and may adjust user interfaces according to various quantitative metrics about the user.

[0123] The user’s past use of user interfaces may be monitored by collecting error rate data (or any other results of an electronic testing activity) associated with various user interfaces. The error rate data may be used to evaluate whether a user is successful in navigating a particular user interface or in selecting a particular control switch. For instance, the BCI system may determine an expected error rate during use of a particular user interface or during selection of a particular control switch. If a user exceeds that error rate, the BCI system may generate an adapted user interface that has a complexity level lower than the previous user interface.

[0124] The BCI may also use data about the user’s past selections on a user interface to guide the design of adaptive user interfaces. For instance, if past use data indicates that a user selects a particular control switch more often than other control switches, an adaptive user interface generated by the BCI system may locate that control switch at a more convenient location in the user interface or may reconfigure the number and type of neural activity to select that control switch.

[0125] Past use data may also be used to determine if a user is fatigued during use of the BCI system. For instance, the BCI may determine an expected number of selections on the user interface over a period of time and compare the expected number of selections with an actual number of selections over the period of time. If the actual number of selections is below a predetermined threshold of expected selections or if the number of selections decreases more than a predetermined amount over a period of time, the BCI may determine that the user is fatigued. The BCI system may then present a user interface with a lower complexity level.Attorney Docket No.: SYNC-N-Z054-00-WO

[0126] A user interface of a B CI system may also be adapted based on data about the user. For instance, the BCI system may monitor the user to determine a parameter about the user, such as physiological data about the user. These parameters may be measured by the BCI system, for instance, using sensors in a neural implant of the BCI system. In other examples, the parameters may be measured using another device, such as a medical testing device or a physical health tracker. In yet further examples, the physiological data may be transmitted to the BCI system from a remote source, such as health data on a server uploaded by the user’s physician. If the parameters are above or below a predetermined threshold, the BCI system may present an adjusted user interface to the user.

[0127] In a particular example, if physiological data about the user (e.g., heart rate, body temperature, blood pressure, breathing rate, pupil dilation, etc.) indicates that the user is fatigued, the BCI system may present a simplified user interface having control switches with a lower level of complexity. If physiological data about the user indicates that the user is undergoing a medical event, an adjusted user interface may be provided with control switches for contacting a healthcare provider or emergency services. In additional aspects, physiological data from the user may indicate that a particular user is having difficulty navigating a user interface and would benefit from a simplified user interface. However, this disclosure is not limited to these particular examples. A BCI system may monitor the user for any other type of data associated with the user and may make adjustments to the user interface according to detected parameters.

[0128] In some examples, adaptive user interfaces may be based on data from other BCI system users. Such data may be useful in the early stages of BCI system use, where the BCI system may lack sufficient user-specific data for generating adaptive user interfaces. For instance, data may be transmitted to the BCI system that indicates that the user has a particular degenerative neurological condition. Data from other users having the same condition may indicate that the user is likely to have a particular ability level for engaging with user interfaces or that their ability level is likely to change over time. The BCI system may then present a user interface to the user based on such data. Demographic data (e.g., the user’s age or primary language etc.) may also be used to generate user interfaces likely to match the user’s ability level and preferences.

[0129] A BCI system may also adapt a user interface based on contextual or environmental parameters, such as the geolocation of the user (determined by, e.g., GPS), the ambient temperature, expected weather at the user’s location, or the time of day. For instance, if the BCI system determines that it is nighttime at the user’s present location, the BCI may decrease the complexity of the user interface or provide a user interface suited for sleep. Such data may beAttorney Docket No.: SYNC-N-Z054-00-WOdetermined by the BCI system or may be transmitted to the BCI system from an external device, such as an associated server. In some aspects, the BCI may use data from an associated personal device to adapt a user interface. For instance, if data from a calendar application on the user’s cell phone indicates the user is likely to be at home, then the BCI may present a user interface suited for at-home use.

[0130] In any of the above examples, Al may be used to improve data analysis. For instance, various data about the user, their ability level, the environment of use, and the user’s past use of user interfaces may be input into an Al model. The Al model may then design an adapted user interface suited to the particular user based on data associated with the user, the environment of use, and the user’s ability level in using user interfaces.

[0131] Al models may also be used to synthesize different types of data over time and in different use cases. For instance, an Al model may determine, based on user testing, that the ability level of the user is a “5”, and that the user has challenges selecting control switches in a particular location on the user interface. Additional data collected during the user’s past use of the BCI system may indicate that the user has difficulty selecting control switches of a particular complexity level at night. Geolocation data about the user may indicate that the user is at home, and such data may be confirmed via a user’s digital calendar in an electronic device associated with the BCI system. Physiological data about the user may indicate that the user’s heart rate is decreasing, indicating the user is likely to be at rest. Additional data input by a healthcare provider may indicate that the user has a progressive neurological condition that may worsen over time, which is confirmed by data collected from similar patient populations that have used the BCI system. The Al model may aggregate such data and use it as inputs in a model to determine a suitable user interface. The Al model may then generate a user interface that is suitable to the particular user’s ability level in a specific condition, time, place, and / or use case present it to the user. However, the use of Al models is not limited to these particular examples. It is anticipated that Al models may accept any data described herein and may use that data to intelligently generate a suitable user interface presented to a user of a BCI system.

[0132] In some aspects, the adaptive user interface systems and methods described herein may employ a quantitative assessment mechanism to determine a numeric score (e.g., a complexity level), referred to herein as a “UI level” or “ability level,” that characterizes the suitable interface complexity (e.g., complexity level) for a given user at a given point in time. This UI level assessment mechanism (e.g., an electronic testing activity), together with a realtime performance monitoring component referred to herein as a “pacing index” (e.g., another electronic testing activity or a result thereof), provides a closed-loop feedback system that continuously and automatically tunes the complexity of the user interface to match the user’sAttorney Docket No.: SYNC-N-Z054-00-WOimmediate capabilities without requiring manual caregiver intervention. Additional detail regarding such mechanisms is included herein, including the manner in which UI levels are assessed, how dynamic UI layout (complexity level) selection and configuration are performed based on the assessed level, how a graduated progression of interface modes (e.g., complexity levels) is implemented, and how the pacing index (e.g., a result of the electronic testing activity) operates to monitor and adjust the UI level (e.g., the complexity level) in real time.

[0133] In some aspects, the BCI system may assess a user’s interface-handling capability by presenting the user with one or more target selection tasks on the user interface and measuring two key metrics: (a) the number of navigation steps for the user to navigate to a target electronic control switch using a navigation tool, referred to herein as the “traversal level,” and (b) the number of selection inputs the user performs to activate or select the target electronic control switch, referred to herein as the “selection level.” As described herein with respect to FIGs. 5A-5B, 6A-6B, 7A-7B, and 8, these metrics may be recorded across various test scenarios and combined to produce a single numeric level score that quantifies the user’s proficiency in handling interface complexity.

[0134] In some aspects, the traversal level for a given electronic control switch may be determined based on an amount of time for the user to navigate to that electronic control switch using the navigation tool, or alternatively based on a quantity of navigation steps or scan cycles to navigate to that electronic control switch. For example, an electronic control switch that requires the navigation tool to traverse a greater number of rows, columns, or other subsets of electronic control switches before reaching the desired switch will have a higher traversal level than a switch that can be reached in fewer navigation steps. As described with respect to FIGs.5A-5B, the traversal level may correspond to the position of a target electronic control switch within a grid of control switches, such that a target in the center of a grid (e.g., the “R5C5” control switch described with respect to FIG. 8) has a higher traversal level than a target in the first row and first column (e.g., the “R1C1” target described with respect to FIG. 8).

[0135] In some aspects, the selection level for a given electronic control switch may be determined based on a quantity of instances of neural activity or other selection inputs to select that electronic control switch. For example, in a multi-action scanner test (e.g., an electronic testing activity) as described with respect to FIG. 9, a target electronic control switch that uses three distinct instances of neural activity to select (e.g., a first instance to select a row of a larger array, a second instance to select a column of the larger array, and a third instance to select within a nested sub-array) will have a higher selection level than a target that uses a single instance of neural activity to select. In some aspects, a weight may be assigned to various forms of neural activity used to select control switches on the user interface, where theAttorney Docket No.: SYNC-N-Z054-00-WOweighting of the selection levels may be based on the difficulty of engaging in the various forms of neural activity. In some examples, the weighting of each form of neural activity is user- specific, based on data about the user’s own competency in engaging in the forms of neural activity.

[0136] In some aspects, the traversal level and selection level for a given electronic control switch may be combined, for example by summing or otherwise mathematically combining them, to produce a single numeric complexity level for that electronic control switch. The overall complexity level of the user interface may then be determined based on the complexity levels of the electronic control switches included on the user interface, for example based on the maximum complexity level among the electronic control switches displayed, or based on an average or weighted average of the complexity levels of a subset of the electronic control switches displayed.

[0137] In some aspects, the UI level assessment (e.g., an electronic testing activity) may be implemented by presenting the user with electronic testing activities of varying complexity, as described herein with respect to FIGs. 5A-5B, 6A-6B, 7A-7B, and 8, and observing the user’s success in selecting target electronic control switches of varying complexity levels. The result of such testing may be an array of candidate level scores, from which the suitable level for the user is identified by finding the highest level at which the user remains comfortable and accurate in selecting target electronic control switches. For example, the user might initially be presented with a target electronic control switch having a complexity level of 12, and the testing activity may adjust upward or downward based on the user’s success — if the user struggles, the testing activity lowers the complexity level of the next target; if the user succeeds, the testing activity may present a target with a higher complexity level — until the testing activity determines the highest complexity level target that the user can reliably select. In a specific example, the testing activity may determine that the user performs comfortably at a level of 10 but struggles at higher levels, such that level 10 is identified as the user’s current capability level. This level score serves as a foundational parameter that drives subsequent UI configuration (which may be an example of or relate to a complexity level).

[0138] In some aspects, the UI level assessment (e.g., an electronic testing activity) may be initiated upon initial setup of the BCI system, according to a predefined schedule, in response to detected selection errors during non-testing use of the BCI system, or in response to a user selection of a testing command switch on the user interface. In some aspects, a model, such as an Al model, may be used to determine which target electronic control switches to prompt the user to select during the testing activity, using as inputs the user’s past success or failure in selecting targets, an error rate, a response time, a traversal level, or a selection level (or anyAttorney Docket No.: SYNC-N-Z054-00-WOother results of electronic testing activity), and outputting a next target electronic control switch or a next navigation complexity (e.g., a next complexity level) for the testing activity.

[0139] In some aspects, once the user’s UI level (e.g., the user’s complexity level) has been determined, the BCI system may automatically select and present an appropriate user interface layout tailored to that level. Each level may correspond to a UI complexity setting that defines a number of interactive electronic control switches shown at once, their arrangement on the user interface, and the navigation method used to navigate between them (e.g., a scanning pattern for switch control). As described herein with respect to FIGs. 4B-4F, the number of electronic control switches displayed on the user interface may be increased or decreased based on the user’s assessed level, such that the user interface is optimized to present the maximum number of communication opportunities without exceeding the user’s comfort threshold.

[0140] For example, a user interface configured at a higher complexity level may accommodate a greater number of electronic control switches in a denser grid arrangement, while a user interface configured at a lower complexity level may present fewer electronic control switches in a more spacious arrangement that is easier to navigate. In a specific example, a user interface configured at a level 10 complexity in a one-dimensional scanning layout could accommodate 16 electronic control switches, compared to only 9 electronic control switches if the user were at a lower complexity level such as level 5. By knowing the user’s level, the BCI system can pack more options into the user interface when appropriate, giving the user a richer set of choices, or conversely reduce the number of options when the level is low to avoid overload.

[0141] In some aspects, the dynamic UI layout (complexity level) selection may also adjust parameters other than the number of electronic control switches, including but not limited to the layout, spacing, density, size, color, contrast, text labels, order, or placement of the electronic control switches, as well as the speed or path of the navigation tool used to navigate among the electronic control switches. In some aspects, a subset of electronic control switches may be selected for display based on a rank or level assigned to each electronic control switch, where the rank or level may be set by the user, a caregiver, or the BCI system itself, as described herein with respect to FIG. 4F.

[0142] In some aspects, the user interface layout may be dynamically adjusted as the user’s assessed level changes over time. As the user’s skills progress (reflected by an increasing level), the BCI system may gradually introduce additional electronic control switches or more intricate layouts. Conversely, if the user’s abilities regress or the user is experiencing fatigue (reflected by a decreasing level), the BCI system may simplify the layout. This adaptabilityAttorney Docket No.: SYNC-N-Z054-00-WQcreates a continuum of user interfaces ranging from very simple to very complex, with the BCI system seamlessly moving the user up and down that continuum based on objective measurements of the user’s performance.

[0143] In some aspects, in addition to adjusting the number and arrangement of electronic control switches within a given layout, the BCI system may define multiple interface modes arranged in tiers of complexity, referred to herein as “interface tiers.” These interface tiers (which may be examples of complexity levels) may range from basic communication boards to advanced keyboard interfaces, providing a graduated progression that allows a user to transition from very limited communication tools to fully flexible communication as their proficiency grows.

[0144] In some aspects, at the lowest interface tier (corresponding to low UI level scores, which may be examples of relatively low complexity levels), the BCI system may limit the user interface to extremely simple outputs, such as a binary-choice interface presenting only “yes” and “no” options, or other minimal-selection interfaces for fundamental communication. For example, at a low level such as level 5, the user’s available interfaces might consist solely of a yes / no board and perhaps a very limited pain scale or other essential input, as described herein with respect to FIGs. 3B and 3C. This ensures that a user who can only handle minimal complexity is presented with an interface they can still use effectively.

[0145] In some aspects, at intermediate interface tiers (corresponding to mid-range UI level scores, which may be examples of mid-range complexity levels), the BCI system may progressively unlock more complex interfaces, including interfaces with a larger number of electronic control switches and tiered keyboard interfaces that introduce sections of the alphabet or commonly used phrases in a step-by-step manner. For example, a mid-level user might be presented with a keyboard arranged in groups of letters rather than a full QWERTY layout, or a grid of electronic control switches arranged by category. The BCI system may use the user’s current level to determine which interface tier is most appropriate at any given time.

[0146] In some aspects, at the highest interface tier (corresponding to high UI level scores, which may be examples of relatively high complexity levels), the BCI system may provide the user with a full QWERTY keyboard interface, potentially augmented with predictive text and advanced language features, such as those provided by a large language model (LLM). At this tier, the user has demonstrated the ability to handle a complete keyboard interface and can form any words or sentences, achieving full expressive communication. In some aspects, when the user reaches the highest interface tier, the BCI system may remove earlier simpler layouts from the display (for example, removing the yes / no board entirely, as it becomes unnecessary andAttorney Docket No.: SYNC-N-Z054-00-WOwould only add extra navigation steps). By eliminating such redundancy, the BCI system reduces clutter and presents only the advanced interface that the user is now capable of using.

[0147] The interface tiers may include at least a binary-choice interface tier, one or more intermediate keyboard interface tiers, and a highest interface tier corresponding to a fullcomplexity interface. The keyboard interface tiers may include a selection of keyboard layouts of varying complexity, such as a QWERTY keyboard, an ABC keyboard, an ABC tiered keyboard, or a vowel-based keyboard, as described herein. The BCI system may select among these keyboard layouts based on the user’s assessed level, transitioning the user interface among the interface tiers as the user’s level changes.

[0148] In some aspects, the graduated progression of interface modes (e.g., complexity levels) may also apply to non-communication interfaces, such as game interfaces or media control interfaces. For example, a game interface may be adapted based on the user’s assessed level by replacing a full-input game control interface with a tiered input interface comprising a reduced set of electronic control switches corresponding to game actions available at the user’s ability level. In a specific example, a user who is unable to handle the full complexity of a particular game interface may be presented with a simplified version of that game interface that uses fewer navigation steps and selection inputs to interact with. Similarly, a media control interface may be simplified to present only the most essential controls (e.g., next, previous, and shuffle) for a user at a low ability level, while presenting a fuller set of controls (e.g., volume, playback speed, playlist navigation) for a user at a higher ability level.

[0149] In some aspects, the graduated system allows a user to transition from very limited communication tools to fully flexible communication, with the BCI system controlling the transitions based on quantifiable performance metrics (the complexity level, such as the UI level) rather than subjective judgment. Because the transitions are determined by demonstrated ability, the user is neither pushed too fast nor held back too long. This is particularly beneficial in assistive technology scenarios where the ultimate goal is often to enable the user to utilize standard off-the-shelf devices or applications. By the time the user consistently operates at the highest interface tier, the BCI system may generate a graduation indicator, as described further below, signaling that the user may be ready to use common user interfaces without special adaptive limitations.

[0150] In some aspects, to ensure the user interface remains optimally configured at all times, the BCI system may implement a real-time performance monitoring (e.g., an electronic testing activity) mechanism referred to herein as a “pacing index.” The pacing index continuously monitors the user’s interaction rate and compares it to a baseline expectedAttorney Docket No.: SYNC-N-Z054-00-WOinteraction rate for the user at the current UI level, providing a real-time feedback signal that drives automatic adjustments to the UI level without requiring manual caregiver intervention.

[0151] In some aspects, the pacing index may be computed based on a “selection strike rate” (SSR), which is a rolling measure of the user’s selection activity relative to the opportunities for selection presented by the user interface. The selection strike rate may be an example of a result of an electronic testing activity. The following describes an example implementation of the pacing index in the context of a scanning interface, such as an iOS switch control interface, where the user is tasked to remain at rest while the navigation tool sweeps through electronic control switches before the focus indicator lands on the selected item. However, the pacing index concept is not limited to scanning interfaces and may be applied to any user interface configuration (and to any determination of complexity level).

[0152] In some aspects, for a scanning interface that sweeps through n electronic control switches before repeating, the BCI system may first calculate an “opportunity weight” (e.g., a result of an electronic testing activity) for each interaction cycle. The opportunity weight represents the effort the user must invest to wait for a chance to make a selection. In some aspects, the opportunity weight may be defined as:opportunity weight = 1 + r(n - 1).

[0153] where n is the number of electronic control switches in the current scan cycle and r is a “rest factor” representing how much each non-selected electronic control switch counts toward the overall effort. The leading 1 represents the single item that is selected, while the term r(n - 1) adds a fraction of the effort for each of the remaining electronic control switches that the user is tasked to rest through without making a selection. Larger scan cycles inflate the opportunity weight, reflecting the greater effort by the user in longer cycles.

[0154] In some aspects, the BCI system may also calculate a “scoring weight” (e.g., a result of an electronic testing activity) for each interaction cycle in which the user makes a selection. The scoring weight represents the credit that a cycle earns when the user successfully selects an electronic control switch. In some aspects, the scoring weight may be defined as: scoring weight = 1 + b(n - 1)

[0155] where b is a “bonus factor” that rewards successful selections in longer, harder cycles. The bonus factor b is greater than the rest factor r, allowing the overall metric to exceed 100% in a manner analogous to a batting strike rate in cricket, where exceptional performance can yield a strike rate above 100.

[0156] In some aspects, as the user continues navigating and making selections, the BCI system may maintain a rolling window of interaction cycles and compute the selection strike rate (SSR) as:Attorney Docket No.: SYNC-N-Z054-00-WOSSR = [ (scoring weights for cycles in which a selection occurred) / (opportunity weights for all cycles in the rolling window)] x 100

[0157] The SSR is thus the sum of scoring weights from cycles in which a selection occurred, divided by the sum of opportunity weights for all cycles in the rolling window, scaled to a per- 100 value. A rising SSR indicates that the user is keeping pace even in tougher cycles, while a falling SSR signals effective fatigue or difficulty

[0158] In some aspects, the pacing index (PI), which may be a result of the electronic testing activity, may be computed by translating the raw SSR into a readable value that represents the user’s effective fatigue or stamina relative to their personal baseline. In some aspects, a personal baseline SSR may be captured at the start of a session or retrieved from a prior session. At each cycle, the BCI system may compute the pacing index as:PI = SSR (current) / SSR (baseline)

[0159] A pacing index of 1 indicates that the user’s current pace matches their baseline performance, while a pacing index of 0.70, for example, indicates that the user is sustaining 70% of their rested performance. The pacing index may thus be interpreted as a measure of the user’s current performance relative to their own established baseline, providing a personalized and objective metric for real-time UI adaptation.

[0160] In some aspects, the BCI system may use the pacing index to automatically adjust the UI level (the complexity level) and corresponding user interface layout during operation. If the user’s pacing index is at or above a first threshold (indicating that the user is comfortably handling the current interface complexity (e.g., complexity level) and keeping up with or exceeding their baseline pace), the BCI system may increase the UI level, for example by adding additional electronic control switches to the display, increasing the density of electronic control switches, or transitioning the user interface to a higher interface tier. Conversely, if the pacing index falls below a second threshold (indicating that the user may be experiencing fatigue or difficulty with the current interface complexity), the BCI system may decrease the UI level, for example by removing electronic control switches from the display, decreasing the density of electronic control switches, or transitioning the user interface to a lower interface tier.

[0161] In some aspects, the BCI system may provide a notification to the user that a modified user interface is available prior to adjusting the UI level, and may receive a user confirmation before making the adjustment. This allows the user to retain autonomy over the adaptation process while still benefiting from the real-time performance monitoring (e.g., an electronic testing activity) provided by the pacing index. In other aspects, the adjustment mayAttorney Docket No.: SYNC-N-Z054-00-WObe performed automatically without requiring user confirmation, providing a fully autonomous adaptation experience.

[0162] In some aspects, the pacing index may also be used to trigger the provision of predictive text or communication assistance on the user interface when the user’s interaction rate falls below the expected interaction rate by more than a threshold amount. For example, if the pacing index indicates that the user is struggling to maintain their baseline interaction rate, the BCI system may display one or more predicted word or phrase completions on the user interface based on the user’s prior interaction history, reducing the selection burden on the user and helping to maintain effective communication even during periods of reduced performance.

[0163] In some aspects, the expected interaction rate used to compute the pacing index may be determined based on a baseline interaction rate established during an initial portion of a session or retrieved from a prior session. In some aspects, the expected interaction rate may be updated over time using an exponential moving average based on one or more prior actual interaction rates, allowing the baseline to adapt gradually to changes in the user’s long-term performance level.

[0164] In some aspects, the pacing index may be computed over a rolling window of one or more interaction cycles, allowing the BCI system to detect short-term fluctuations in the user’s performance that may indicate transient fatigue or difficulty, as well as longer-term trends that may indicate more sustained changes in the user’s ability level. The size of the rolling window may be configurable, for example by the user or a caregiver, to balance responsiveness to short-term fluctuations against stability in the face of random variation.

[0165] In some aspects, the BCI system may provide an “additive display mode” (also referred to herein as an “agentic mode”) as an alternative to the leveling mode described herein. In the additive display mode, rather than changing the existing base arrangement of electronic control switches on the user interface, the BCI system may selectively add an additional region or pane to the display that includes alternative electronic control switches suited to the user’s current ability level, without modifying the base arrangement. This approach allows the user to retain access to their familiar base interface while also being offered a simplified alternative when the BCI system determines that the base arrangement exceeds the user’s current capability.

[0166] In some aspects, the additive display mode may be enabled via a control setting on the user interface, for example through a settings menu. When the additive display mode is enabled, the leveling mode that would otherwise change the base arrangement may be disabled, such that the base arrangement remains fixed while the BCI system monitors the user’s interaction with the base arrangement and determines whether to add the additional region orAttorney Docket No.: SYNC-N-Z054-00-WOpane. In some aspects, the user’s preference for the additive display mode may be stored and applied in subsequent sessions, and the user may provide an input to dismiss the additional region or pane after it has been added.

[0167] In some aspects, the electronic user interface may provide one or more mechanisms by which the user may dismiss the additional region or pane after it has been added to the display. For example, the additional region or pane may include a dedicated dismiss control switch that, when selected by the user, causes the additional region or pane to be removed from the display without affecting the base arrangement. In some aspects, the BCI system may automatically dismiss the additional region or pane after a predefined timeout period has elapsed without any user interaction with the alternative electronic control switches in the additional region or pane, on the basis that the user has returned to a sufficient level of performance with the base arrangement. In some aspects, the BCI system may dismiss the additional region or pane in response to determining that the user's pacing index has recovered above the threshold at which the additional region or pane was triggered, indicating that the user is once again able to interact effectively with the base arrangement without supplemental assistance. In some aspects, the user may also dismiss the additional region or pane by selecting a dismiss control switch on the base arrangement itself, for example a designated settings or close control switch already present in the base arrangement, such that no additional navigation burden is imposed on the user to effect the dismissal. In some aspects, the user's dismissal of the additional region or pane may be recorded as a preference signal, such that the BCI system leams over time whether the user tends to engage with or dismiss the additional region or pane when it is presented, and may adjust the threshold at which the additional region or pane is triggered accordingly.

[0168] In some aspects, the additional region or pane added in the additive display mode may include simplified electronic control switches relative to the electronic control switches of the base arrangement. For example, the additional region or pane may include an additional row of electronic control switches corresponding to a simplified keyboard interface, a binarychoice interface, a simplified game interface, or a media control interface. In some aspects, the alternative electronic control switches may include context-based suggestions determined based on the current screen or application associated with the user interface, where the contextbased suggestions may be generated using a language mode.

[0169] In some aspects, the BCI system may determine that the base arrangement exceeds the capability of the user based on the user’s interaction with the base arrangement while the additive display mode is enabled. For example, the BCI system may determine that the user fails to select a desired electronic control switch within a time threshold, or that an error rateAttorney Docket No.: SYNC-N-Z054-00-WOassociated with selection exceeds an error threshold. In some aspects, this determination may be made using the pacing index described herein, as follows.

[0170] In some aspects, the BCI system may operate the user interface as a scanning interface that sequentially highlights a plurality of electronic control switches in interaction cycles, and may compute, over a rolling window of interaction cycles, a selection strike rate as described herein. The BCI system may then compute a pacing index based on the ratio of the selection strike rate relative to a baseline selection strike rate for the user, and may determine that the base arrangement exceeds the capability of the user when the pacing index falls below a threshold. In response to this determination, the BCI system may add the additional region or pane including the alternative electronic control switches to the display without changing the base arrangement.

[0171] In some aspects, the BCI system may implement a graduation mechanism that generates a graduation indicator when the user has demonstrated sustained ability to interact with the user interface at the highest interface tier across a threshold quantity of sessions. The graduation indicator may indicate a recommendation for the user to transition to a non-adapting user interface that operates without complexity adjustment based on an ability level of the user, such as a standard off-the-shelf device or application.

[0172] In some aspects, the threshold quantity of sessions may include a predetermined quantity of consecutive sessions in which the user has consistently interacted with the user interface at the highest interface tier. For example, the BCI system may expect the user to demonstrate consistent performance at the highest interface tier across three, five, or ten consecutive sessions before generating the graduation indicator. In some aspects, the BCI system may generate a consistency score (e.g., a result of an electronic testing activity) based on the user’s interaction with the user interface at the highest interface tier across a plurality of sessions, and may trigger the generation of the graduation indicator when the consistency score exceeds a graduation threshold.

[0173] In some aspects, determining whether the user has interacted with the user interface at the highest interface tier may include determining that at least one of a response time, an accuracy, a reproducibility of the neural activity, or an error rate associated with interaction at the highest interface tier (each of which may be examples of results of an electronic testing activity) meets or exceeds a performance threshold across the threshold quantity of sessions. In some aspects, the graduation indicator may include a visual notification displayed on the user interface, an auditory notification, or both. In some aspects, the BCI system may transmit the graduation indicator to a caregiver or clinician associated with the user, for example via aAttorney Docket No.: SYNC-N-Z054-00-WOnetwork connection to a remote server, to inform the caregiver or clinician that the user may be ready to transition to a more advanced or standard user interface.

[0174] In some aspects, the graduation indicator provides a clear, objective milestone for transitioning the user to greater independence, which previously was difficult to determine without extensive subjective observation by trained professionals. By quantifying the user’s performance using the UI level and pacing index metrics (each of which may be examples of complexity levels and / or testing results) described herein, the BCI system can objectively determine when the user has reached a level of proficiency sufficient to use mainstream communication applications or standard operating system interfaces without special adaptive limitations.

[0175] In some aspects, the integration of the UI level assessment mechanism (e.g., an electronic testing activity), dynamic UI layout (complexity level) selection, graduated progression of interface modes (e.g., complexity levels), pacing index, additive display mode, and graduation indicator described herein results in a fully automated adaptive user interface system. The BCI system may continuously self-optimize the user interface without requiring external input from a caregiver or clinician, aside from the user’s own interactions with the user interface. In some aspects, the BCI system may include a manual override mechanism, such as a slider or other control in a settings menu, that allows a caregiver or clinician to manually adjust the UI level (e.g., a complexity level) when desired, for example on a particularly difficult day for the user. However, for the most part, the adaptation process is automatic, allowing the user to benefit from a continuously optimized user interface without waiting for a caregiver to make adjustments.

[0176] In some aspects, the automated adaptation provided by the BCI system may be particularly beneficial in scenarios where the user’s abilities vary significantly from day to day, for example due to fatigue, the progression of a neurological condition, or other factors. By continuously monitoring the user’s interaction rate and adjusting the UI level in real time, the BCI system can increase the likelihood that the user has access to the most capable interface they can handle at any given moment, while also providing a simplified interface during periods of reduced performance. This dynamic autonomy is beneficial for scaling the technology to many users, since a single caregiver can only manage a limited number of individuals if each requires constant custom UI adjustment. With automation, the BCI system can be deployed to many users with confidence that each interface is self-calibrating in real time.

[0177] In some aspects, the quantitative metrics generated by the UI level assessment and pacing index mechanisms (e.g., electronic testing activities) may also provide valuable insightsAttorney Docket No.: SYNC-N-Z054-00-WOinto the user’s performance and progress over time. For example, steadily increasing level scores or consistently high pacing indices may indicate skill acquisition, while declining metrics may indicate the need (e.g., a request) for clinical attention or adjustments in therapy. The availability of these objective metrics may reduce the reliance on subjective judgment by caregivers and clinicians when making decisions about the user’s interface configuration (e.g., complexity level) and readiness to transition to more advanced interfaces.

[0178] In some aspects, the BCI system may also incorporate an intelligent content management module, such as a large language model (LLM), to adapt the content presented on the user interface according to the user’s UI level and context. At lower levels, the content presented on the user interface may be restricted to essential or simple vocabulary, while at higher levels more extensive vocabulary and predictive text suggestions may be provided, enhancing communication efficiency at each level. The LLM may learn the user’s preferences and frequently used phrases over time, making communication faster and more personalized. In some aspects, the LLM may generate a set of electronic control switches for display on the user interface based on the current application or screen associated with the user interface, providing context-sensitive suggestions that are tailored to the user’s current communication needs and ability level.

[0179] In some aspects, the adaptive user interface system described herein is designed to operate independently of the particular input modality used by the user to make selections on the user interface. That is, the system treats the user interface as existing in an isolated context in which the system does not concern itself with the mechanism by which the user generates selection inputs, but rather focuses on whether the user is able to make selections as easily and reliably as possible given the current interface configuration (e.g., the current complexity level). External factors (including the user’s fatigue, emotional state, pain level, engagement level, and the specific input modality in use) may be treated as parameters that collectively determine the size and complexity of the interface the user can reliably handle at a given moment, rather than as separately tracked variables. The system may abstract away from the underlying input mechanism and focus on the resulting interaction performance as reflected by the UI level and pacing index.

[0180] In some aspects, this input-modality independence means that the adaptive user interface system described herein may be employed with any assistive input modality, including but not limited to a BCI system that detects neural activity as described herein, an eye tracking system that detects gaze direction or dwell time, a mouse or trackpad, a joystick, a sip-and-puff controller, an inertial sensor that detects body movement, a camera-based movement detector, or any other input mechanism capable of generating selection inputs on aAttorney Docket No.: SYNC-N-Z054-00-WOuser interface. The UI level assessment mechanism, pacing index, graduated interface progression, and all other adaptive mechanisms described herein (that is, any of the electronic testing activities described herein) may operate in the same manner regardless of the input modality in use, as they measure the user’s ability to navigate to and select electronic control switches (a metric that is input-modality agnostic).

[0181] In some aspects, the input-modality independence of the adaptive user interface system provides particular advantages in scenarios where a user’s available input modality changes unexpectedly or temporarily. For example, a user who normally employs a combination of eye tracking and BCI input may experience a temporary reduction in eye tracking accuracy (for example, due to the administration of eye drops that cause blurred vision or pupil dilation). In such a scenario, the user may switch to BCI-only input mode, and the adaptive user interface system may respond by adjusting the UI level and interface configuration (e.g., complexity level) to account for the reduced input precision available in that mode (for example, by presenting larger electronic control switches, reducing the density of the display, or transitioning to a lower interface tier). Because the system does not require or use knowledge of the specific input modality in use, this transition may occur seamlessly and automatically based solely on the user’s observed interaction performance, without requiring manual reconfiguration by a caregiver or clinician.

[0182] Such aspects may also provide advantages in terms of scalability and generalizability of the adaptive user interface system. Because the system is not coupled to any particular input modality or device type, a single implementation of the adaptive user interface system can serve users across a wide range of assistive technology configurations. This makes the system particularly well-suited for deployment in diverse clinical and home settings where users may have different input modalities available at different times.

[0183] In some aspects, in addition to the traversal level and selection level metrics described herein, the BCI system may also measure a throughput metric (e.g., a result of an electronic testing activity) during the UI level assessment (e.g., an electronic testing activity) and during ongoing use of the user interface. As used herein, throughput refers to the rate at which the user is able to successfully convey information through the user interface, for example measured in bits per second or selections per unit time. Throughput may be used as a standard metric for evaluating the performance of assistive technology users and may be used as a supplementary data point during the UI level assessment (e.g., the electronic testing activity) described herein.

[0184] In some aspects, however, throughput alone does not capture the full picture of a user’s ability to interact with a given user interface configuration (e.g., a given complexityAttorney Docket No.: SYNC-N-Z054-00-WOlevel). Throughput measures the overall rate of information transfer but does not independently capture the two distinct dimensions of interaction difficulty that are reflected by the traversal level and selection level (namely, the difficulty of navigating to a desired electronic control switch and the difficulty of activating that switch once reached). For example, two users may achieve the same throughput on a given user interface, but one user may achieve that throughput by making rapid but inaccurate selections (high traversal speed, low selection accuracy) while the other achieves it by making slow but highly accurate selections (low traversal speed, high selection accuracy). The traversal level and selection level metrics described herein capture these distinct dimensions of interaction difficulty independently, allowing the BCI system to design user interfaces that are specifically suited for each user’s particular profile of strengths and limitations, in a manner that throughput alone may not support.

[0185] The traversal level and selection level metrics may therefore be used in conjunction with throughput as complementary metrics, with throughput providing a high-level summary of overall interaction efficiency and the traversal and selection levels providing a more granular characterization of the specific dimensions of interaction difficulty that drive the user’s UI level. In some aspects, the BCI system may use throughput data collected during the UI level assessment (e.g., an intentional electronic testing activity) or during ongoing use (e.g., a passive electronic testing activity) of the user interface as an additional input to the Al model described herein, alongside the traversal level, selection level, error rate, and / or other metrics associated with results of an electronic testing activity, to further refine the determination of the user’s UI level and the selection of an appropriate user interface configuration (e.g., an appropriate complexity level).

[0186] In some aspects, in addition to the grid-based target selection tests described herein with respect to FIGs. 5A-5B, 6A-6B, 7A-7B, and 8, the BCI system may implement an alternative testing modality in which the user is presented with a target word or phrase and prompted to spell out the word or phrase by sequentially selecting each letter or character as a target on the user interface. In this modality, each individual character of the target word or phrase serves as a sequential target for the purposes of the UI level assessment (e.g., the electronic testing activity), such that the BCI system can gather traversal level and selection level data for each character target in the context of what appears to the user to be a natural communication task rather than an abstract grid test.

[0187] In some aspects, for example, the BCI system may present the user with a target word such as “brain” and prompt the user to spell the word by selecting the letters B, R, A, I, and N in sequence on the user interface. Each letter selection provides the BCI system withAttorney Docket No.: SYNC-N-Z054-00-WOdata about the traversal level and selection level to reach and select that particular character on the user interface, which may vary depending on the position of the character on the keyboard layout currently displayed and the navigation method in use. The BCI system may aggregate the traversal level and selection level data collected across all character targets in the target word or phrase to determine or update the user’s UI level, in the same manner as described herein for grid-based testing.

[0188] The target word or phrase testing modality (e.g., an electronic testing activity) provides several advantages. First, because the testing activity takes the form of a natural spelling task, the user may find it more engaging and less fatiguing than other tests, potentially improving the quality and reliability of the data collected. Second, the target word or phrase testing modality allows the BCI system to collect UI level data during what appears to the user to be ordinary communication use of the user interface, rather than having the user engage in a dedicated testing protocol. This may allow the BCI system to collect UI level data more frequently and with less disruption to the user’s normal use of the interface. Third, the target word or phrase testing modality naturally generates traversal level and selection level data that is specific to the keyboard layout and navigation method currently in use, providing data that is directly relevant to the user’s actual interface configuration (e.g., actual complexity level).

[0189] In some aspects, the target word or phrase used in the testing modality may be selected by the BCI system, for example using an Al model that selects target words or phrases that provide good coverage of the range of traversal levels and selection levels available on the current user interface. In other aspects, the target word or phrase may be selected by a caregiver or clinician, or may be drawn from a predefined list of test words or phrases. In some aspects, the BCI system may present the target word or phrase visually on the user interface as a prompt to the user, and may provide feedback to the user after each character selection to indicate whether the selection was correct, in a same or similar manner as described herein for grid-based testing.

[0190] In some aspects, after the user’s initial UI level has been established through the grid-based or target word testing activity described herein, the BCI system may update the UI level over time using an exponential moving average (EMA) mechanism. The EMA mechanism allows the BCI system to gradually shift the user’s UI level up or down in response to new performance data collected during ongoing use of the user interface, while giving greater weight to the established baseline level and lesser weight to individual data points that may reflect transient fluctuations in the user’s performance.

[0191] In some aspects, the EMA-based level update mechanism may be described as follows. The user’s initial UI level, determined through the testing activity described herein,Attorney Docket No.: SYNC-N-Z054-00-WOserves as the starting point or anchor for the EMA. As the user continues to interact with the user interface, the BCI system collects performance data (including traversal level data, selection level data, error rate data, and / or pacing index data, each of which may be a result of an electronic testing activity) and uses this data to compute an updated UI level at regular intervals. The updated UI level is computed as a weighted average of the current UI level and the performance-implied level derived from the new data (e.g., derived from or an example of one or more results of an electronic testing activity), where the weighting is controlled by a smoothing parameter that determines how sensitive the level is to change from the established baseline.

[0192] In some aspects, the smoothing parameter of the EMA may be configurable, for example by a caregiver or clinician through a settings menu, to control the rate at which the UI level responds to new performance data. A higher smoothing parameter (giving more weight to new data) results in a UI level that responds more quickly to changes in the user’s performance, which may be desirable for users whose abilities fluctuate rapidly. A lower smoothing parameter (giving more weight to the established baseline) results in a UI level that is more stable and less responsive to transient fluctuations, which may be desirable for users whose abilities are relatively stable over time. In some aspects, the BCI system may automatically select an appropriate smoothing parameter based on the variability of the user’s past performance data, for example by selecting a higher smoothing parameter for users whose performance data shows high variability and a lower smoothing parameter for users whose performance data shows low variability.

[0193] In some aspects, the EMA-based level update mechanism operates in parallel with the pacing index described herein. While the pacing index provides a real-time, within-session feedback signal that drives immediate adjustments to the UI level during a session, the EMA mechanism provides a longer-term update to the baseline UI level that persists across sessions and reflects the user’s overall trajectory of improvement or decline. Together, the pacing index and EMA mechanism provide a two-timescale adaptation system: the pacing index handles rapid, within-session fluctuations in the user’s performance, while the EMA handles slower, cross-session trends in the user’s ability level.

[0194] In some aspects, the user or a caregiver may initiate a new grid-based or target word testing activity at any time to reset or recalibrate the UI level, for example if the user’s abilities have changed significantly since the last testing activity. In such cases, the result of the new testing activity may replace the current EMA-based level as the new anchor for subsequent EMA updates, allowing the system to quickly adapt to significant changes in the user’s ability level without waiting for the EMA to gradually converge to the new level.Attorney Docket No.: SYNC-N-Z054-00-WO

[0195] In some aspects, while the adaptive user interface system described herein is designed to operate autonomously without requiring manual intervention by a caregiver or clinician during normal use, the BCI system may include a manual override mechanism accessible through a settings menu that allows a caregiver, clinician, or Field Clinical Engineer (FCE) to manually adjust the UI level when desired. In some aspects, this manual override mechanism may take the form of a slider control displayed within the settings menu of the user interface, which allows the caregiver or FCE to quickly and intuitively adjust the UI level by dragging the slider to a desired position corresponding to a desired complexity level.

[0196] In some aspects, the slider control may display the full range of available UI levels, for example from a minimum level corresponding to the lowest interface tier (e.g., a binary yes / no interface) to a maximum level corresponding to the highest interface tier (e.g., a full QWERTY keyboard interface). As the caregiver or FCE drags the slider to a new position, the user interface may update in real time to reflect the interface configuration corresponding to the selected level (e.g., the selected complexity level), allowing the caregiver or FCE to preview the interface that will be presented to the user before committing to the adjustment. This realtime preview capability allows the caregiver or FCE to quickly identify an appropriate level for the user without requiring trial and error.

[0197] In some aspects, the manual override via the settings slider may be particularly useful on days when the user is experiencing unusual difficulty or fatigue that the automated pacing index mechanism has not yet detected, or when a caregiver or FCE has clinical knowledge about the user’s current condition that is not reflected in the user’s interaction data. For example, if a user is having a particularly difficult day and the caregiver wishes to immediately simplify the interface without waiting for the pacing index to detect the decline in performance, the caregiver may use the settings slider to manually lower the UI level to a more appropriate setting. Similarly, if a user has recently undergone a therapy session or other intervention that has improved their abilities, the caregiver may use the settings slider to manually raise the UI level to reflect the user’s improved capabilities.

[0198] In some aspects, when a manual override is applied via the settings slider, the BCI system may record the manually set level as a new anchor for the EMA-based level update mechanism described herein, such that subsequent automated adjustments are made relative to the manually set level rather than the previously established baseline. In other aspects, the manual override may be treated as a temporary adjustment that does not affect the EMA baseline, such that the system gradually returns to the EMA-derived level over time as new performance data is collected. The behavior of the system following a manual override may be configurable through the settings menu.Attorney Docket No.: SYNC-N-Z054-00-WO

[0199] In some aspects, access to the settings slider and manual override functionality may be restricted to authorized users, such as caregivers, clinicians, or FCEs, to prevent inadvertent or unauthorized changes to the user’s interface configuration. For example, the settings menu containing the slider may be protected by a passcode or other authentication mechanism that is entered before the slider can be adjusted. In other aspects, the settings slider may be accessible to the user themselves, allowing the user to manually adjust their own UI level if they prefer a different complexity level than the one automatically determined by the system.

[0200] In some aspects, the adaptive user interface system described herein may include a modular game board component that provides a reusable, adaptable game interface whose complexity is automatically adjusted based on the user’s assessed UI level. The modular game board component is designed such that the same underlying board structure and component architecture can be reused across multiple different game types, with the complexity of the board (including the number of tiles, the keyboard layout used for text input, the number of available game actions, and other parameters) adjusted based on the user’s current UI level.

[0201] In some aspects, the modular game board component may be used to implement a variety of different game types on the user interface, including but not limited to word games (such as a Wordle-style game in which the user attempts to guess a target word by entering letter guesses), trivia games (such as a multiple-choice trivia game powered by a language model that generates questions and evaluates answers), and other text-based or selection-based games. Despite the different gameplay mechanics of these game types, the underlying modular game board component provides a consistent structure that can be adapted to each game type by configuring the appropriate game-specific parameters, while the complexity adjustment mechanism operates in the same manner across all game types based on the user’s UI level.

[0202] In some aspects, the complexity of the modular game board may be adjusted based on the user’s UI level in multiple dimensions simultaneously. For example, in a word game implementation, the complexity adjustment may include selecting a keyboard layout of appropriate complexity for the user’s level (e.g., a full QWERTY keyboard at high levels, a tiered keyboard at intermediate levels, or a vowel-focused keyboard at lower levels), adjusting the number of guesses or attempts available to the user, adjusting the length of the target word, or adjusting the number of tiles displayed on the game board. In a trivia game implementation, the complexity adjustment may include selecting questions of appropriate difficulty, adjusting the number of answer choices presented, or adjusting the time available for the user to make a selection. In some aspects, the specific complexity parameters adjusted for a given game type may be configured by a caregiver or clinician through the settings menu, allowing the complexity adjustment to be tailored to the specific requirements of each game.Attorney Docket No.: SYNC-N-Z054-00-WO

[0203] In some aspects, the modular game board architecture provides a significant advantage in terms of development efficiency and consistency of the user experience across different game types. Because the same underlying board component is reused across multiple game types, improvements to the complexity adjustment mechanism — such as updates to the UI level assessment algorithm or the pacing index — automatically benefit all game types that use the modular board component, without requiring separate updates to each game implementation. Similarly, the consistent board structure across game types means that users who are familiar with the interface of one game type can quickly adapt to other game types that use the same board component, reducing the learning curve associated with new games.

[0204] In some aspects, the modular game board component may also include a language model integration that generates game content (such as trivia questions, word prompts, or other game-specific content) based on the user’s current UI level and context. For example, a trivia game powered by a language model may generate questions of appropriate difficulty for the user’s current level, ensuring that the game remains engaging and achievable regardless of the user’s ability level. In some aspects, the language model may also adapt the vocabulary and phrasing of game content to be appropriate for the user’s communication level, further enhancing the accessibility of the game interface.

[0205] In some aspects, the graduated progression of interface modes (e.g., complexity levels) described herein may be illustrated by a specific example involving a media control interface for a user who wishes to control a music player using the BCI system. This example demonstrates the real-world motivation for the graduated interface progression and illustrates how the system can increase the likelihood that a user has access to at least some level of meaningful interaction with their environment, even on days when their abilities are significantly reduced.

[0206] In some aspects, consider a user who relies on a BCI system for interaction with their environment and who has a personal music collection as a primary source of enjoyment and engagement. This user’s abilities may vary significantly from day to day. For example, on good days, the user may be able to navigate a relatively complex media control interface with multiple electronic control switches, while on difficult days the user may only be able to reliably generate a single selection input. Without an adaptive interface system, such a user might be left with either an interface that is too complex to use on difficult days, or an interface that is unnecessarily limited on good days.

[0207] In some aspects, the graduated media control interface may be configured to present the user with a progressively more complex set of media control options as their UI level increases, as follows. At the lowest interface tier (corresponding to the user’s minimumAttorney Docket No.: SYNC-N-Z054-00-WQability level), the media control interface may present a single electronic control switch that, when selected, shuffles the user’s music collection to play a random track. This single-switch shuffle interface requires only one selection input and zero navigation steps, making it accessible even on the user’s most difficult days. At the next interface tier, the media control interface may present two electronic control switches corresponding to “next track” and “previous track” controls, allowing the user to navigate forward and backward through their music collection. At higher interface tiers, additional controls may be progressively added, such as volume up and volume down controls, a mute control, a pause and play control, a playlist navigation control, and other media controls. At the highest interface tier, the user may have access to a full media control interface with all available controls, potentially including the ability to search for specific artists, albums, or tracks by spelling out their names using the keyboard interface.

[0208] In some aspects, the transitions between these media control interface tiers may be driven by the same UI level and pacing index mechanisms described herein, such that the media control interface automatically simplifies on days when the user is struggling and automatically expands on days when the user is performing well. This increases the likelihood that the user has access to the most capable media control interface they can reliably use at any given moment, without requiring manual reconfiguration by a caregiver. In some aspects, the specific media controls available at each interface tier may be configured by the user or a caregiver through the settings menu, allowing the graduated media control interface to be tailored to the user’s specific preferences and needs.

[0209] In some aspects, in addition to the full QWERTY keyboard, ABC keyboard, ABC tiered keyboard, and vowel-based keyboard variants described herein, the BCI system may also provide a reduced QWERTY keyboard variant as one of the available keyboard layouts in the graduated keyboard interface progression. The reduced QWERTY keyboard variant presents a subset of the keys available on a full QWERTY keyboard in a QWERTY-style spatial arrangement, such that users who are familiar with the QWERTY layout can benefit from that familiarity while interacting with a keyboard that has a lower overall complexity level than a full QWERTY keyboard.

[0210] In some aspects, the reduced QWERTY keyboard may omit less frequently used keys (such as punctuation keys, number keys, or function keys) while retaining the alphabetic keys in their standard QWERTY positions. This allows users at intermediate UI levels to benefit from the spatial familiarity of the QWERTY layout without being required to navigate a full-complexity keyboard. In some aspects, the specific keys included in the reduced QWERTY keyboard may be configurable by the user or a caregiver, for example to include orAttorney Docket No.: SYNC-N-Z054-00-WQexclude specific punctuation marks or special characters based on the user’s communication needs.

[0211] In some aspects, the reduced QWERTY keyboard variant occupies an intermediate position in the graduated keyboard interface progression, between the tiered keyboard variants (which require fewer navigation steps but may be less familiar to users accustomed to QWERTY layouts) and the full QWERTY keyboard (which provides the most complete set of keys but requires the highest UI level). The availability of the reduced QWERTY variant as a distinct interface tier provides an additional step in the graduated progression that may be particularly beneficial for users who are transitioning from a tiered keyboard to a full QWERTY keyboard, as it allows them to become familiar with the QWERTY spatial layout at a lower complexity level before advancing to the full keyboard. As with the other keyboard variants described herein, the BCI system may select the reduced QWERTY keyboard for display based on the user’s assessed UI level, transitioning to or from this variant as the user’s level changes.

[0212] In some aspects, the UI level adjustment mechanism described herein operates in a continuous and real-time manner, such that the user interface transitions smoothly between complexity levels rather than making abrupt jumps between discrete interface configurations. For example, two interface configurations may represent relatively different complexity levels, such that there is a relatively large increase in complexity level from one interface configuration to the next. UI level adjustments may involve relatively smaller changes in complexity level, such that UI level adjustments may allow for smaller increases in complexity level as compared to an interface configuration change, for at least some complexity levels. As the user’s UI level changes (whether due to the pacing index detecting a change in the user’s interaction rate, the EMA mechanism updating the baseline level, or a manual override via the settings slider) the user interface updates in real time to reflect the new complexity level, presenting the user with an interface configuration that corresponds to the new level without requiring the user to navigate to a different screen or initiate any action.

[0213] In some aspects, the real-time, continuous nature of the level adjustment may be particularly apparent when a caregiver or FCE uses the settings slider to manually adjust the UI level, as described herein. As the slider is moved from one position to another, the user interface may update continuously to reflect the interface configuration at each intermediate level, providing a live preview of the interface at each level as the slider passes through it. This continuous update behavior allows the caregiver or FCE to observe the full range of available interface configurations in real time and to select the most appropriate level for the user with precision and confidence.Attorney Docket No.: SYNC-N-Z054-00-WO

[0214] In some aspects, the continuous nature of the level adjustment also means that the transition between interface tiers (for example, the transition from a tiered keyboard to a full QWERTY keyboard as the user’s level increases) may be implemented as a smooth progression rather than an abrupt switch. For example, the BCI system may gradually introduce additional keys to the keyboard display as the user’s level increases, adding keys in order of their complexity level (as defined by their traversal level and selection level) until the full keyboard is displayed. This gradual introduction of additional keys allows the user to become familiar with the expanding keyboard interface incrementally, rather than being confronted with a sudden increase in complexity. In some aspects, the rate at which additional keys are introduced during a level transition may be configurable through the settings menu, allowing the transition to be made more or less gradual depending on the user’s preferences and the caregiver’s clinical judgment.

[0215] In some aspects, the adaptive user interface systems and methods described herein may be understood as implementing a closed-loop three-stage framework that operates continuously during use of the BCI system. The three stages of this framework are: (1) a presentation stage, in which one or more activities, stimuli, or interactive tasks are presented to the user on the electronic user interface; (2) an evaluation stage (e.g., an electronic testing activity), in which the user’s ability level or BCI literacy is evaluated based on the user’s interaction with the presented activities or stimuli; and (3) an adaptation stage, in which one or more parameters of the electronic user interface, the BCI system, or the user’s training schedule are adjusted based on the evaluated ability level. The framework may loop back continuously. For example, the output of the adaptation stage feeds back into the presentation stage, such that the adapted user interface itself becomes the context in which the next round of evaluation occurs. This closed-loop, continuously iterating structure differs from static or onetime assessment approaches, in which a user’s ability level is assessed once, and the interface is configured accordingly without further automated adjustment.

[0216] In some aspects, the presentation stage of the three-stage framework may encompass any of the testing modalities (e.g., any of the electronic testing activities) described herein, including grid-based target selection tests as described with respect to FIGs. 5A-5B, 6A-6B, 7A-7B, and 8, target word or phrase tests, moving or dynamically repositioning target tests, and passive monitoring during activities of daily living. In some aspects, the evaluation stage may encompass any of the ability level determination mechanisms described herein (e.g., any of the electronic testing activities described herein), including the traversal level and selection level assessment, the pacing index computation, the EMA-based level update, and the BCI literacy score derivation. In some aspects, the adaptation stage may encompass any of theAttorney Docket No.: SYNC-N-Z054-00-WOUI adaptation mechanisms described herein, including dynamic UI layout (complexity level) selection, graduated interface tier progression, additive display mode, decoder parameter adjustment, and training schedule adjustment. The three-stage framework thus provides a unifying conceptual structure that encompasses all of the adaptive mechanisms described herein and that can be applied across a wide range of user populations, input modalities, and use cases.

[0217] In some aspects, the closed-loop nature of the three-stage framework provides an advantage over other approaches in which interface configuration (e.g., complexity level selection) was performed statically or used manual intervention by a caregiver or clinician. In some approaches, a user’s interface is configured once at setup and remained fixed until a caregiver manually reconfigured it, or was reconfigured following a periodic offline assessment. The present system, by contrast, continuously evaluates the user’s ability level and adapts the interface in real time, increasing the likelihood that the interface is suitably configured for the user’s current capabilities without requiring any human intervention. This continuous, automated adaptation is the core distinguishing feature of the present system and is what enables the system to serve users across the full range of their ability levels, from initial setup through long-term use and eventual graduation to a standard interface.

[0218] In some aspects, the UI level score described herein may constitute a quantitative BCI literacy score (e.g., a result of an electronic testing activity), which may be a single numeric value that objectively characterizes a user’s current proficiency in interacting with a BCI system or other assistive technology interface. As described herein, BCI literacy refers to an individual’s proficiency in effectively operating BCI systems, encompassing the ability to generate distinguishable brain signals, comprehend system feedback, and adapt to the BCI’s operational protocols. The UI level score described herein provides a concrete, objective, and continuously updated quantification of this BCI literacy concept, translating what has historically been a subjective clinical judgment into a numeric score that can be tracked, compared, and acted upon automatically by the BCI system.

[0219] In some aspects, the UI level score may serve as a BCI literacy score that is derived from the user’s demonstrated ability to navigate to and select electronic control switches of varying complexity levels, as measured by the traversal level and selection level metrics described herein. A higher UI level score indicates a higher degree of BCI literacy (the user is able to reliably handle more complex interfaces requiring more navigation steps and more selection inputs). A lower UI level score indicates a lower degree of BCI literacy (the user is only able to reliably handle simpler interfaces with fewer navigation steps and fewer selection inputs). In some aspects, the BCI literacy score may be updated continuously over time usingAttorney Docket No.: SYNC-N-Z054-00-WOthe EMA-based level update mechanism described herein, such that the score reflects the user’s current ability level rather than a historical snapshot.

[0220] In some aspects, the availability of a quantitative BCI literacy score (e.g., a result of an electronic testing activity) provides several benefits that were not previously achievable with subjective or qualitative assessments of user ability. First, the BCI literacy score provides an objective basis for selecting an appropriate user interface configuration (e.g., complexity level) for the user, eliminating the guesswork and subjectivity that have historically characterized this process. Second, the BCI literacy score provides a common metric that can be used to track a user’s progress over time, compare performance across sessions, and identify trends that may indicate skill acquisition or decline. Third, the BCI literacy score provides a clear, objective threshold for determining when a user is ready to transition to a more advanced interface or to a standard off-the-shelf device, as described herein with respect to the graduation indicator mechanism. Fourth, the BCI literacy score provides a standardized metric that could in principle be used to compare ability levels across different users, different BCI systems, and different input modalities, enabling population-level analysis of BCI literacy that was not previously possible with subjective assessments.

[0221] In some aspects, the UI level score may be expressed as a numeric value within a predefined range, such as a range from 0 to 20, where 0 corresponds to the lowest interface tier (e.g., a binary yes / no interface requiring minimal navigation and selection) and the maximum value (e.g., 20) corresponds to the highest interface tier (e.g., a full QWERTY keyboard interface requiring the maximum navigation and selection complexity available in the system). This numeric range provides an intuitive and easily interpretable scale for the BCI literacy score, allowing caregivers, clinicians, and users to quickly understand a user’s current ability level and track their progress toward the maximum level. In some aspects, the specific numeric range used may be configurable, for example by a system administrator or caregiver, to accommodate different interface configurations or user populations.

[0222] In some aspects, in addition to adapting the user interface layout and content based on the user’s assessed UI level, the BCI system may also adapt one or more neural signal processing parameters based on the user’s assessed UI level or ability level. As described herein, the BCI system may change the algorithm used to process signals representative of the neural activity of the user, for example to allow selection of an electronic control switch with more precise or less precise signals, or to change the algorithm that maps the neural activity to selection of electronic control switches based on the ability level.

[0223] In some aspects, the neural signal processing parameters that may be adapted based on the UI level include, but are not limited to, the sensitivity of the neural signal decoder (i.e.,Attorney Docket No.: SYNC-N-Z054-00-WOthe threshold at which a neural signal is interpreted as an intentional selection input), the selectivity of the neural signal decoder (i.e., the degree to which the decoder distinguishes between different types of neural signals), the switch profile of the BCI system (i.e., the set of neural signal types and thresholds used to map neural activity to selection inputs), and other parameters of the signal processing pipeline that affect the accuracy, reliability, and responsiveness of the BCI system’s interpretation of the user’s neural activity.

[0224] In some aspects, adapting the neural signal processing parameters based on the UI level may be particularly beneficial on days when the user’s neural signals are weaker, less consistent, or more variable than usual (for example, due to fatigue, the progression of a neurological condition, or other factors). In such cases, the BCI system may adjust the sensitivity of the neural signal decoder to be more responsive to weaker signals, reducing the threshold at which a neural signal is interpreted as an intentional selection input and thereby compensating for the reduced signal quality. Conversely, on days when the user’s neural signals are strong and consistent, the BCI system may adjust the decoder to be more selective, reducing the likelihood of false positive selections caused by unintentional neural activity.

[0225] In some aspects, the adaptation of neural signal processing parameters may be performed in conjunction with the adaptation of the user interface layout, such that both the interface configuration and the signal processing pipeline are simultaneously optimized for the user’s current ability level. For example, on a day when the user’s UI level is low (indicating reduced performance), the BCI system may both simplify the user interface layout (by reducing the number and complexity of electronic control switches displayed) and adjust the neural signal decoder (by increasing its sensitivity to compensate for weaker signals), providing a comprehensive adaptation that addresses both the interface-level and signal-level dimensions of the user’s reduced performance.

[0226] In some aspects, in addition to adapting the user interface layout and neural signal processing parameters, the BCI system may also adapt a training schedule for the user based on the user’s assessed UI level or ability level. As used herein, a training schedule refers to a plan or program of testing activities, calibration sessions, or other interactive tasks presented to the user on the electronic user interface for the purpose of improving or maintaining the user’s BCI literacy and proficiency in interacting with the BCI system, each of which may be an example of an electronic testing activity.

[0227] In some aspects, the training schedule may be adapted based on the user’s current UI level in multiple dimensions, including the frequency of training sessions, the duration of each training session, the complexity of the testing activities presented during training, and the specific skills or interaction modalities targeted by the training activities. For example, a user atAttorney Docket No.: SYNC-N-Z054-00-WOa low UI level may be presented with more frequent and shorter training sessions focused on simple target selection tasks, to build basic proficiency in navigating and selecting electronic control switches without overwhelming the user. As the user’s UI level increases, the training schedule may be adapted to present less frequent but more challenging training sessions that target more complex interaction skills, such as navigating multi-level menus or selecting targets in dense grid arrangements.

[0228] In some aspects, the adaptation of the training schedule may be performed automatically by the BCI system based on the user’s current UI level and the trajectory of their level over time, as reflected by the EMA-based level update mechanism described herein. For example, if the user’s UI level has been increasing steadily over a period of time, the BCI system may automatically reduce the frequency of training sessions (on the basis that the user is progressing well and does not require intensive training) and increase the complexity of the testing activities presented during training (to continue challenging the user and promoting further skill development). Conversely, if the user’s UI level has been declining or stagnating, the BCI system may automatically increase the frequency of training sessions and reduce the complexity of the testing activities to help the user rebuild or maintain their proficiency.

[0229] In some aspects, the training schedule adaptation may also take into account the user’s pacing index during training sessions, adjusting the difficulty and duration of training activities in real time based on the user’s current performance relative to their baseline. For example, if the pacing index indicates that the user is performing well during a training session, the BCI system may extend the session or introduce more challenging activities; if the pacing index indicates that the user is fatiguing, the BCI system may shorten the session or reduce the complexity of the remaining activities. This real-time adaptation of training activities ensures that each training session is optimally productive for the user, increasing skill development while reducing fatigue and frustration.

[0230] In some aspects, in addition to the grid-based target selection tests and target word or phrase tests (e.g., an electronic testing activity) described herein, the BCI system may implement a third assessment modality (e.g., another electronic testing activity) in which the user’s UI level is assessed passively and continuously during the user’s ordinary activities of daily living using the electronic user interface, without requiring the user to engage in any dedicated testing protocol. In this passive assessment modality, the BCI system continuously monitors the user’s interaction with the electronic user interface during normal, non-testing use and derives UI level data from the user’s observed interaction performance, in the same manner as described herein for the pacing index mechanism.Attorney Docket No.: SYNC-N-Z054-00-WO

[0231] In some aspects, the passive continuous assessment modality may be distinguished from the pacing index mechanism in the following way: while the pacing index provides a realtime, within-session feedback signal that drives immediate adjustments to the UI level during a session, the passive continuous assessment modality provides a longer-term, cross-session assessment of the user’s ability level that is derived from the aggregate of the user’s interaction performance across multiple screens, applications, and use contexts during ordinary daily use. The passive continuous assessment thus captures a broader and more representative sample of the user’s interaction performance than any single testing session or pacing index computation, providing a more robust and reliable estimate of the user’s true ability level.

[0232] In some aspects, the passive continuous assessment modality may be implemented by the BCI system analyzing a plurality of screens or applications that the user interacts with during ordinary daily use and determining, for each screen or application, whether the user is able to reliably navigate to and select the electronic control switches displayed on that screen or application. For example, if the user interacts with a keyboard interface during ordinary use, the BCI system may analyze the user’s traversal level and selection level data for each key selected on the keyboard and use this data to update the user’s UI level estimate. Similarly, if the user interacts with a menu interface or a game interface during ordinary use, the BCI system may analyze the user’s interaction performance on that interface and use this data to update the UI level estimate.

[0233] In some aspects, the passive continuous assessment modality may be particularly valuable in scenarios where the user is unable or unwilling to engage in dedicated testing protocols, for example due to fatigue, time constraints, or personal preference. By deriving UI level data from the user’s ordinary daily use of the electronic user interface, the passive continuous assessment modality allows the BCI system to maintain an up-to-date estimate of the user’s ability level without imposing any additional burden on the user. This is consistent with the broader goal of the present system of reducing the need for manual caregiver intervention and increasing user autonomy and independence.

[0234] In some aspects, the BCI system may implement an alternative testing modality in which a target electronic control switch is dynamically repositioned on the user interface during the testing activity, and the user is prompted to navigate to and select the target at each new position. This testing modality (e.g., an electronic testing activity) may be referred to herein as a “moving target test” or a “chase-a-target test,” as the user continuously tracks and / or chases the target as it moves to different positions on the user interface.

[0235] In some aspects, during a moving target test (e.g., an electronic testing activity), the target electronic control switch may be repositioned to a sequence of different positions on theAttorney Docket No.: SYNC-N-Z054-00-WOuser interface, for example moving through different quadrants or sections of the user interface in a predefined or randomized order. At each new position, the user is prompted to navigate to and select the target, and the BCI system records the traversal level and selection level data for each target selection. The BCI system may aggregate the traversal level and selection level data collected across all target positions during the moving target test to determine or update the user’s UI level, in the same manner as described herein for grid-based testing and target word or phrase testing.

[0236] In some aspects, the moving target test provides several advantages. First, because the target moves to different positions on the user interface during the test, the moving target test can collect traversal level and selection level data across a wider range of positions on the user interface in a single continuous testing session, providing more comprehensive coverage of the user interface than a test that prompts the user to select only a limited number of fixed targets. Second, the moving target test may be more engaging, as the continuously changing target position requires the user to actively track the target rather than simply waiting for a target to be highlighted. This increased engagement may improve the quality and reliability of the data collected during the test. Third, the moving target test more closely simulates the dynamic nature of real-world interaction with the electronic user interface, in which the user is tasked to navigate to targets at varying positions depending on the current screen and application, providing a more ecologically valid assessment of the user’s ability level as compared to some other tests.

[0237] In some aspects, the BCI system may implement the moving target test using the same user interface and navigation tool as described herein for stationary grid-based testing, with the target electronic control switch highlighted or otherwise visually distinguished at each new position to prompt the user to navigate to and select it. In some aspects, the sequence of target positions during the moving target test may be determined by an Al model that selects positions providing good coverage of the range of traversal levels and selection levels available on the current user interface, in the same manner as described herein for the Al-driven target selection in grid-based testing. In other aspects, the sequence of target positions may be predefined or randomized, or may be selected by a caregiver or clinician.

[0238] In some aspects, the combination of the initial UI level assessment, the EMA-based level update mechanism, and the real-time pacing index described herein (e.g., each of which may be an example of an electronic testing activity) together constitute a three-timescale closed-loop adaptation system that continuously updates the user interface at distinct temporal scales simultaneously. The timescales of this adaptation system include: (1) the within-cycle timescale, at which the pacing index is updated after each individual interaction cycle and mayAttorney Docket No.: SYNC-N-Z054-00-WOtrigger immediate adjustments to the UI level; (2) the within-session timescale, at which the pacing index is computed over a rolling window of interaction cycles and drives session-level adjustments to the UI level; and (3) the cross-session timescale, at which the EMA-based level update mechanism aggregates performance data across multiple sessions to update the baseline UI level.

[0239] In some aspects, the three -timescale adaptation system provides a comprehensive and robust response to changes in the user’s ability level across all relevant temporal scales. Short-term fluctuations in the user’s performance (such as transient fatigue during a single session) are detected and addressed by the within-cycle and within-session pacing index mechanisms, which can trigger immediate simplification of the user interface before the user becomes overwhelmed. Uonger-term trends in the user’s performance (such as gradual skill acquisition over weeks or months, or gradual decline due to the progression of a neurological condition) are detected and addressed by the cross-session EMA mechanism, which updates the baseline UI level to reflect the user’s overall trajectory. Together, these timescales ensure that the user interface is suitably configured for the user’s current capabilities, regardless of whether those capabilities are changing rapidly or slowly, temporarily or permanently.

[0240] In some aspects, this three-timescale adaptation stands in contrast to other approaches, which may only address a single timescale of adaptation (for example, adjusting scan timing (which may be an example of or relate to a complexity level) within a session based on error rates, or performing a one-time offline assessment to configure the interface at setup). By addressing all three timescales simultaneously within a single unified system, the described techniques provide a level of adaptive responsiveness and long-term improvement.

[0241] FIG. 10 shows a block diagram of an example processing device 1000 that supports adaptive user interfaces for brain-computer interface systems in accordance with one or more aspects of the present disclosure. The processing device 1000 may be any computing device configured to implement the adaptive user interface systems and methods described herein, including but not limited to a signal control unit, a host device, a tablet, a smartphone, a headset device (e.g., an extended or virtual reality headset device), a dedicated BCI controller, or any other computing device capable of communicating with a neural interface device, presenting an electronic user interface to a user of a BCI system, and / or communicating (via a wired and / or wireless connection) with a device capable of presenting an electronic user interface to a user of a BCI system. For example, the processing device 1000 may be an example of the signal control unit 104 or the electronic device 202 described with reference to FIGs. 1 and 2. The processing device 1000, or various components thereof, may be an example of means for performing various aspects of the adaptive user interface methods describedAttorney Docket No.: SYNC-N-Z054-00-WOherein, including providing and adjusting the electronic user interface, performing electronic testing activities, monitoring user interaction, computing the pacing index, updating the UI level, and generating graduation indicators, as described herein.

[0242] The processing device 1000 may be configured or configurable to communicate with one or more components of a BCI system, including a neural interface device configured to detect neural activity from a brain of a user, a transmitter and receiver unit configured to transmit electronic signals representative of the neural activity to the processing device 1000, and one or more electronic devices with which the user interacts via the electronic user interface. In some examples, the processing device 1000 may be configured to communicate with such components wirelessly, for example via a wireless communication protocol, or via a wired connection. In some examples, the processing device 1000 may be configured to communicate with a remote server, for example to access databases of user-specific data or program data for adjusting the adaptive user interface, as described with reference to FIG. 2.

[0243] A processing device 1000 may include one or more chips, system on chips (SoCs), chipsets, packages, components, or devices that individually or collectively constitute or include a processing system 1005. A processing system 1005 may interface with other components of the processing device 1000 and may generally process information (such as inputs or signals) received from such other components and output information (such as outputs or signals) to such other components. As shown in FIG. 10, the processing device 1000 includes a processing system 1005 that includes processor circuitry 1010 (such as one or more processor circuits or circuitry, processing circuitry, or a processor) and memory circuitry 1015 (such as one or more memory circuits or circuitry, or a memory).

[0244] The processing system 1005 is configured to cause the processing device 1000 to perform various operations described herein, including providing a display on the electronic user interface, providing electronic testing activities, monitoring user interaction with the electronic user interface, computing traversal levels and selection levels, determining UI levels and BCI literacy scores, computing the pacing index and selection strike rate, updating the UI level using the EMA mechanism, adjusting the complexity level of the electronic user interface, implementing the additive display mode, generating graduation indicators, and all other adaptive user interface operations described herein. In this context, “configured to cause” may refer to the processing system 1005 being operable to, adapted to, or otherwise enabled (such as by the processor circuitry 1010 executing instructions or code loaded from the memory circuitry 1015) to cause or enable the processing device 1000 to perform the operations. In some examples, “configured to cause” may refer to the processing system 1005 being operable to perform an operation (or enable the operation to be performed) directly orAttorney Docket No.: SYNC-N-Z054-00-WOindirectly by way of hardware, firmware, software, or an operational state of the processing system 1005. In some examples, the operations may involve the processing system 1005 causing or enabling the processing device 1000 to communicate with a neural interface device, a transmitter and receiver unit, or one or more electronic devices associated with the BCI system via the antenna system 1035 or via a wired connection.

[0245] Processor circuitry 1010 may be collectively configured to perform signal processing operations associated with receiving and interpreting neural activity signals from the neural interface device, adaptive user interface operations associated with determining and adjusting the complexity level of the electronic user interface, and any other operations described herein. Processor circuitry 1010 may be implemented in the form of one or multiple processors, microprocessors, application processors, host processors, processing units (such as central processing units (CPUs), graphics processing units (GPUs), neural processing units (NPUs) (also referred to as neural network processors or deep learning processors (DUPs)), data processing units (DPUs), tensor processing units (TPUs), or digital signal processors (DSPs)), processing blocks, application-specific integrated circuits (ASICs), programmable logic devices (PUDs), or other discrete gate or transistor logic or circuitry (each of which may be generally referred to herein individually as “a processor” or “processor circuitry 1010”). One or more processors of processor circuitry 1010 may be individually or collectively configurable or configured to perform various functions or operations described herein. In some examples, the processor circuitry 1010 may include one or more processors configured to execute a language model or other Al model for use in generating adaptive user interface content, computing UI level scores, or performing other Al-driven operations described herein.

[0246] Memory circuitry 1015 may be collectively configured for storing, accessing, or retrieving stored information at the request of processor circuitry 1010, including information associated with the adaptive user interface operations described herein. For example, memory circuitry 1015 may store user-specific data including a user’s current UI level or BCI literacy score, baseline selection strike rate, EMA smoothing parameters, traversal level and selection level data, error rate data, pacing index history, interface tier configurations, keyboard layout configurations, game board configurations, training schedule data, and any other data described herein as being stored or retrieved by the BCI system. Generally, components of memory circuitry 1015 may be coupled with components of processor circuitry 1010 and individually or collectively store processor-executable code that, when executed by the processor circuitry 1010, may configure or enable the processor circuitry 1010 to perform various operations described herein. However, in some examples, some of the processor circuitry 1010 may beAttorney Docket No.: SYNC-N-Z054-00-WOpreconfigured to perform various operations described herein without requiring configuration or enablement by code stored in the memory circuitry 1015.

[0247] Memory circuitry 1015 may be implemented in the form of one or more memory devices, memory components, memory blocks, memory elements, or other discrete gate or transistor logic or circuitry. Memory circuitry 1015 may include tangible storage media including non-volatile memory, such as read-only memory (ROM), or volatile memory, such as random-access memory (RAM) (such as static RAM (SRAM), dynamic RAM (DRAM), or synchronous DRAM (SDRAM) such as low power double data rate (LPDDR) memory, among other examples, each of which may be generally referred to herein individually as “a memory” or “memory circuitry 1015”). In some examples, a processing system 1005, and processor circuitry 1010 within it, may also be coupled with memory circuitry outside of or distinct from the processing system 1005. For example, such additional memory circuitry may include a nonvolatile memory storage device such as a solid state drive (SSD), a hard disk drive (HDD), or removable storage media. In some other examples, additional memory circuitry may also include volatile memory such as SRAM, DRAM, SDRAM, or LPDDR memory, among other examples.

[0248] Processor circuitry 1010 may be coupled directly or indirectly with memory circuitry 1015 via an interface 1030 (such as one or more interfaces). An interface 1030 may include any suitable quantities or types of interconnecting buses, bridges, or circuitry depending on the specific applications and overall design constraints. In some examples, some or all of the processor circuitry 1010 may be interconnected together within one chip, SoC, or package. Such a chip, SoC, or package may also include memory circuitry 1015 integrated within it. In some other examples, a processing system 1005 may include any suitable combination of two or more distinct chips, SoCs, chipsets, packages, components, or devices, each of which may include respective processor circuitry 1010 or memory circuitry 1015, or both.

[0249] A processing device 1000 may also include any additional circuitry or components for processor circuitry 1010 to operate to perform the functions and processes described herein related to the adaptive user interface. For example, as is also shown in FIG. 10, a processing system 1005 may be directly or indirectly coupled with an antenna system 1035 that includes one or more antennas, which may be in the form of one or more individual antenna elements, antenna arrays, or antenna panels, among other examples. The antenna system 1035 may be used to support wireless communication between the processing device 1000 and one or more components of the BCI system, including the neural interface device, the transmitter and receiver unit, one or more electronic devices associated with the BCI system, or one or moreAttorney Docket No.: SYNC-N-Z054-00-WOremote servers storing user-specific data or program data for the adaptive user interface. In some examples, the processing device 1000 may communicate with such components using any suitable wireless communication protocol, including but not limited to Bluetooth, Wi-Fi, or a cellular communication protocol. In some examples, the processing device 1000 may additionally, or alternatively, communicate with such components via a wired connection, such as a USB connection or a proprietary wired interface.

[0250] In some examples, the processing device 1000 may include or be coupled with one or more display components configured to present the electronic user interface to the user of the BCI system. For example, the processing device 1000 may be coupled with a video display, a touchscreen display, a projector, or any other display device capable of presenting the electronic user interface described herein. The display component may be configured to present the electronic control switches, navigation tools, keyboard interfaces, game interfaces, media control interfaces, testing activity prompts, pacing index indicators, graduation indicators, settings menus, and all other visual elements of the electronic user interface described herein. In some examples, the display component may be integrated within the processing device 1000 (for example, as a screen on a tablet or smartphone serving as the host device for the BCI system) or may be a separate device coupled with the processing device 1000.

[0251] In some examples, the processing device 1000 may include or be coupled with one or more input components configured to receive inputs from a caregiver, clinician, or Field Clinical Engineer (FCE) for purposes of manual override of the UI level, configuration of the adaptive user interface settings, or other administrative functions described herein. For example, the processing device 1000 may include or be coupled with a touchscreen, a keyboard, a mouse, or any other input device capable of receiving the settings slider input, passcode entry, or other caregiver inputs described herein. In some examples, such input components may be the same display component used to present the electronic user interface to the user, for example where the processing device 1000 is a tablet or smartphone with a touchscreen display that serves both as the display for the user’s electronic user interface and as the input device for caregiver configuration.

[0252] FIG. 11 shows a block diagram 1100 of an example adaptive user interface device 1120 that supports adaptive user interfaces for brain-computer interface systems in accordance with one or more aspects of the present disclosure. The adaptive user interface device 1120 may be any computing device configured to implement the adaptive user interface systems and methods described herein, including but not limited to a signal control unit, a host device, a tablet, a smartphone, or a dedicated BCI controller. For example, the adaptive user interface device 1120 may be an example of aspects of the signal control unit 104 or the electronicAttorney Docket No.: SYNC-N-Z054-00-WOdevice 202 described with reference to FIG.s 1 and 2. The adaptive user interface device 1120, or various components thereof, may be an example of means for performing various aspects of the adaptive user interface methods described herein. For example, the adaptive user interface device 1120 may include a display component 1125, a user testing component 1130, a user monitoring component 1135, or any combination thereof. The display component 1125 may be configured to provide and adjust the electronic user interface displayed to the user, including presenting electronic control switches, navigation tools, keyboard interfaces, game interfaces, media control interfaces, testing activity prompts, pacing index indicators, graduation indicators, and settings menus.

[0253] The user testing component 1130 may be configured to provide electronic testing activities to the user, including grid-based target selection tests, target word or phrase tests, and moving target tests, and to collect traversal level and selection level data from the user’s engagement with those testing activities. The user monitoring component 1135 may be configured to monitor the user’s interaction with the electronic user interface during both testing and non-testing use, including monitoring the user’s actual interaction rate for purposes of computing the pacing index, monitoring the user’s performance for purposes of updating the UI level using the EMA mechanism, and monitoring the user’s interaction at the highest interface tier for purposes of generating the graduation indicator. Each of these components, or components or subcomponents thereof, may communicate directly or indirectly with one another and with the processing system 1005 described with reference to FIG. 10.

[0254] The display component 1125 is capable of, configured to, or operable to support a means for providing a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display. The user testing component 1130 is capable of, configured to, or operable to support a means for providing an electronic testing activity for the neural activity on the electronic user interface. In some examples, the display component 1125 is capable of, configured to, or operable to support a means for adjusting the complexity level of the display based on a result of the electronic testing activity.

[0255] In some examples, the user monitoring component 1135 is capable of, configured to, or operable to support a means for monitoring the electronic testing activity during engagement by the user, where adjusting the complexity level is in accordance with monitoring the electronic testing activity during the engagement by the user.

[0256] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for increasing orAttorney Docket No.: SYNC-N-Z054-00-WOdecreasing a quantity of the set of multiple electronic control switches displayed on the electronic user interface.

[0257] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for changing at least one of a layout, a spacing, a density, a size, a color, a contrast, a text label, an order, or a placement of one or more of the set of multiple electronic control switches.

[0258] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for changing at least one of a speed or a path of a navigation tool for the user to navigate among the set of multiple electronic control switches.

[0259] In some examples, to support providing the electronic testing activity, the user testing component 1130 is capable of, configured to, or operable to support a means for prompting the user to select a target electronic control switch displayed on the electronic user interface.

[0260] In some examples, to support prompting the user to select the target electronic control switch, the user testing component 1130 is capable of, configured to, or operable to support a means for iteratively prompting the user to select additional target electronic control switches having. In some examples, to support prompting the user to select the target electronic control switch, the user testing component 1130 is capable of, configured to, or operable to support a means for increased navigation complexity (e.g., increased complexity level) in response to a successful selection of a prior target electronic control switch. In some examples, to support prompting the user to select the target electronic control switch, the user testing component 1130 is capable of, configured to, or operable to support a means for decreased navigation complexity (e.g., decreased complexity level) in response to an unsuccessful selection of a prior target electronic control switch.

[0261] In some examples, the result of the electronic testing activity includes at least one of a response time, an accuracy, a reproducibility of the neural activity, or an error rate associated with a selection of one or more target electronic control switches.

[0262] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for selecting, as the set of multiple electronic control switches for display, a subset of electronic control switches having complexity levels not exceeding an ability level determined based on the electronic testing activity.

[0263] In some examples, to support selecting the subset of electronic control switches, the display component 1125 is capable of, configured to, or operable to support a means forAttorney Docket No.: SYNC-N-Z054-00-WOselecting the subset of electronic control switches such that a complexity level of the display, computed based on a maximum, an average, or a weighted average of complexity levels of electronic control switches in the subset of electronic control switches, does not exceed the ability level.

[0264] In some examples, a complexity level of an electronic control switch is based on a traversal level and a selection level. In some examples, the traversal level is based on an amount of time or a quantity of navigation steps for navigating to the electronic control switch. In some examples, the selection level is based on a quantity of instances of the neural activity to select the electronic control switch.

[0265] In some examples, to support providing the electronic testing activity, the user testing component 1130 is capable of, configured to, or operable to support a means for initiating the electronic testing activity at least one of upon initial setup of the brain-computer interface, according to a schedule, in response to detected selection errors during non-testing use, or in response to a user selection of a testing command switch.

[0266] In some examples, to support providing the electronic testing activity, the user testing component 1130 is capable of, configured to, or operable to support a means for using a model to determine which target electronic control switches from a group of target electronic control switches to prompt the user to select.

[0267] In some examples, the model uses an input of at least one of prior success or failure in selecting targets, an error rate, a response time, a traversal level, or a selection level, and outputs at least one of a next target electronic control switch or a next navigation complexity (e.g., a next complexity level).

[0268] In some examples, the electronic user interface is configured to adjust the complexity level of the display by increasing or decreasing a navigation complexity (e.g., increasing or decreasing a complexity level) for the user to navigate the set of multiple electronic control switches displayed by the electronic user interface.

[0269] In some examples, the neural activity includes an endogenous signal representative of neural activity detected by a neural interface device.

[0270] In some examples, the display component 1125 is capable of, configured to, or operable to support a means for providing a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display. The user monitoring component 1135 is capable of, configured to, or operable to support a means for monitoring the user while engaging the electronic user interface to determine an ability level of the user to interact withAttorney Docket No.: SYNC-N-Z054-00-WOthe electronic user interface using the neural activity. In some examples, the display component 1125 is capable of, configured to, or operable to support a means for adjusting the complexity level of the set of multiple electronic control switches displayed by the electronic user interface based on the ability level of the user.

[0271] In some examples, to support determining the ability level (e.g., an electronic testing activity), the user monitoring component 1135 is capable of, configured to, or operable to support a means for determining at least one of a response time for selection of an electronic control switch, an accuracy of selection of an electronic control switch, a reproducibility of neural activity used for selection, or an error rate for selection.

[0272] In some examples, the ability level corresponds to a highest complexity level of an electronic control switch that the user is able to reliably select with less than a threshold error rate.

[0273] In some examples, to support determining the ability level (e.g., an electronic testing activity), the user monitoring component 1135 is capable of, configured to, or operable to support a means for providing an electronic testing activity that prompts selection of one or more target electronic control switches having different navigation complexities. In some examples, to support determining the ability level, the user monitoring component 1135 is capable of, configured to, or operable to support a means for determining the ability level based on a performance in the electronic testing activity.

[0274] In some examples, to support determining the ability level (e.g., an electronic testing activity), the user monitoring component 1135 is capable of, configured to, or operable to support a means for determining a numerical level score (e.g., a result of the electronic testing activity) based on a combination of (i) a quantity of navigation steps to reach each of the one or more target electronic control switches, and (ii) a quantity of selection inputs to select each of the one or more target electronic control switches.

[0275] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for displaying a subset of the set of multiple electronic control switches that excludes electronic control switches having complexity levels exceeding the ability level.

[0276] In some examples, the electronic user interface includes a keyboard interface. In some examples, adjusting the complexity level includes selecting a keyboard layout from a set of keyboard layouts including at least two of a QWERTY keyboard, an ABC keyboard, an ABC tiered keyboard, or a vowel-based keyboard.

[0277] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for transitioningAttorney Docket No.: SYNC-N-Z054-00-WOthe electronic user interface among interface tiers that include at least a binary-choice interface tier and a keyboard interface tier.

[0278] In some examples, transitioning among the interface tiers includes displaying a binary-choice board including “yes” and “no” at a first tier of the interface tiers and displaying a full keyboard at a second tier of the interface tiers.

[0279] In some examples, the display component 1125 is capable of, configured to, or operable to support a means for removing the binary-choice board from the display when the second tier is displayed.

[0280] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for changing an order or placement of an electronic control switch on the electronic user interface based on a frequency of selection of the electronic control switch.

[0281] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for changing at least one of a start position or a path of a navigation tool for the user to navigate among the set of multiple electronic control switches based on a frequency of selection of one or more electronic control switches.

[0282] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for changing an algorithm used to process signals representative of the neural activity of the user to allow selection of an electronic control switch with more precise or less precise signals.

[0283] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for changing an algorithm that maps the neural activity to selection of the set of multiple electronic control switches based on the ability level.

[0284] In some examples, adjusting the complexity level is performed automatically without caregiver intervention, and the display component 1125 is capable of, configured to, or operable to support a means for limiting an adjustment of the complexity level based on a maximum complexity level.

[0285] In some examples, the ability level includes a literacy score derived from at least one of a response time, an accuracy, a reproducibility of the neural activity, or an error rate associated with interaction with the electronic user interface across a set of multiple sessions.

[0286] In some examples, the literacy score includes a brain-computer interface (BCI) literacy score.Attorney Docket No.: SYNC-N-Z054-00-WO

[0287] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for unlocking one or more interface capabilities of the electronic user interface in response to the ability level meeting or exceeding a literacy score threshold.

[0288] In some examples, to support monitoring the user, the user monitoring component 1135 is capable of, configured to, or operable to support a means for monitoring the user while the user performs one or more activities of daily living using the electronic user interface, where the ability level is derived at least in part from a performance of the user during the one or more activities of daily living.

[0289] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for modifying a structure of the game interface based on the ability level of the user.

[0290] In some examples, to support modifying the structure of the game interface, the display component 1125 is capable of, configured to, or operable to support a means for replacing a full-input game control interface with a tiered input interface including a reduced set of electronic control switches corresponding to game actions available at the ability level of the user.

[0291] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for generating one or more predictive control suggestions for display on the electronic user interface based on the ability level of the user and a predicted next interaction of the user with the electronic user interface.

[0292] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for generating a set of electronic control switches for display on the electronic user interface using a language model, where the set of electronic control switches is generated based on a current application or screen associated with the electronic user interface.

[0293] In some examples, the display component 1125 is capable of, configured to, or operable to support a means for providing an electronic user interface for interacting with an electronic device using a set of multiple electronic control switches displayed by the electronic user interface, where the electronic user interface can adjust a complexity level of a display of one or more of the set of multiple electronic control switches. In some examples, the user monitoring component 1135 is capable of, configured to, or operable to support a means for monitoring a parameter associated with a user when the user engages the electronic user interface. In some examples, the display component 1125 is capable of, configured to, orAttorney Docket No.: SYNC-N-Z054-00-WOoperable to support a means for adjusting the complexity level of the set of multiple electronic control switches displayed based on the parameter associated with the user.

[0294] In some examples, the parameter associated with the user includes a physiological parameter selected from a heart rate, a body temperature, a blood pressure, a breathing rate, or a pupil dilation.

[0295] In some examples, the parameter associated with the user includes a location of the user. In some examples, adjusting the complexity level includes presenting control switches associated with a location-specific task.

[0296] In some examples, the parameter associated with the user includes a time of day. In some examples, adjusting the complexity level includes decreasing the complexity level at nighttime.

[0297] In some examples, the parameter associated with the user includes at least one of an error rate or a response time associated with selection of the set of multiple electronic control switches during non-testing use.

[0298] In some examples, the parameter associated with the user includes a use history indicating a frequency of selection of one or more electronic control switches. In some examples, adjusting the complexity level includes relocating at least one of the one or more electronic control switches.

[0299] In some examples, the parameter associated with the user includes an ability level of the user to interact with the electronic user interface.

[0300] In some examples, monitoring the parameter associated with the user includes receiving the parameter from at least one of an external device, a personal electronic device, or a remote server.

[0301] In some examples, adjusting the complexity level is based on aggregating a set of multiple parameters associated with the user to determine the complexity level.

[0302] In some examples, the electronic user interface can operate with a brain-computer interface. In some examples, each of the set of multiple electronic control switches is selectable using a neural activity of the user.

[0303] In some examples, the parameter associated with the user includes a braincomputer interface literacy score derived from at least one of a response time, an accuracy, a reproducibility of a neural activity, or an error rate associated with interaction with the electronic user interface across a set of multiple sessions.

[0304] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for unlocking oneAttorney Docket No.: SYNC-N-Z054-00-WOor more interface capabilities of the electronic user interface in response to the parameter meeting or exceeding a literacy threshold.

[0305] In some examples, to support monitoring the parameter associated with the user, the user monitoring component 1135 is capable of, configured to, or operable to support a means for monitoring the user while performing one or more activities of daily living using the electronic user interface, where the parameter is derived at least in part from a performance of the user during the one or more activities of daily living.

[0306] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for modifying a structure of the game interface based on the parameter associated with the user.

[0307] In some examples, to support modifying the structure of the game interface, the display component 1125 is capable of, configured to, or operable to support a means for replacing a full-input game control interface with a tiered input interface including a reduced set of electronic control switches corresponding to game actions available based on the parameter associated with the user.

[0308] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for generating one or more predictive control suggestions for display on the electronic user interface based on the parameter associated with the user and a predicted next interaction of the user with the electronic user interface.

[0309] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for generating a set of electronic control switches for display on the electronic user interface using a language model, where the set of electronic control switches is generated based on a current application or screen associated with the electronic user interface.

[0310] In some examples, the display component 1125 is capable of, configured to, or operable to support a means for providing an electronic user interface that includes a set of multiple electronic control switches and a navigation tool for guiding navigation among the set of multiple electronic control switches. In some examples, the user monitoring component 1135 is capable of, configured to, or operable to support a means for determining a traversal level for at least one electronic control switch based on an amount of time for a user to navigate to the at least one electronic control switch using the navigation tool. In some examples, the user monitoring component 1135 is capable of, configured to, or operable to support a means for determining a selection level for the at least one electronic control switch based on a quantity of instances of a selection input by the user to select the at least one electronic controlAttorney Docket No.: SYNC-N-Z054-00-WOswitch. In some examples, the display component 1125 is capable of, configured to, or operable to support a means for adjusting the electronic user interface to be associated with a complexity level that is based on the traversal level and the selection level.

[0311] In some examples, the user monitoring component 1135 is capable of, configured to, or operable to support a means for determining the complexity level for the electronic user interface based on a combination of the traversal level and the selection level.

[0312] In some examples, the display component 1125 is capable of, configured to, or operable to support a means for determining the complexity level based on a maximum complexity level among the set of multiple electronic control switches displayed or based on an average or weighted average of complexity levels of a subset of the set of multiple electronic control switches displayed.

[0313] In some examples, the navigation tool includes an indicator, an effector, or a cursor that is displayed on the electronic user interface and that guides navigation among the set of multiple electronic control switches.

[0314] In some examples, to support determining the traversal level, the user monitoring component 1135 is capable of, configured to, or operable to support a means for determining a quantity of navigation steps or scan cycles to navigate to the at least one electronic control switch using the navigation tool.

[0315] In some examples, the selection input includes neural activity of the user.

[0316] In some examples, to support determining the selection level, the user monitoring component 1135 is capable of, configured to, or operable to support a means for applying a weight to a selection input type of the selection input based on a difficulty of engaging in the selection input type.

[0317] In some examples, the weight is user specific.

[0318] In some examples, to support adjusting the electronic user interface, the display component 1125 is capable of, configured to, or operable to support a means for selecting a subset of electronic control switches for display based on a rank or level assigned to each electronic control switch, where the rank or level is set by at least one of the user, a caregiver, or the electronic user interface.

[0319] In some examples, the user testing component 1130 is capable of, configured to, or operable to support a means for determining the traversal level and the selection level during an electronic testing activity that prompts selection of one or more target electronic control switches.

[0320] In some examples, the electronic testing activity includes a single-switch scanner test or a multi-action scanner test (each of which may be examples of an electronic testingAttorney Docket No.: SYNC-N-Z054-00-WOactivity) that uses different forms of neural activity to access different rows, columns, or subsets of electronic control switches.

[0321] In some examples, to support adjusting the electronic user interface, the display component 1125 is capable of, configured to, or operable to support a means for transitioning among interface tiers including a binary-choice interface tier and a keyboard interface tier, including selecting a keyboard layout from a set of keyboard layouts including at least two of a QWERTY keyboard, an ABC keyboard, an ABC tiered keyboard, or a vowel-based keyboard.

[0322] In some examples, the display component 1125 is capable of, configured to, or operable to support a means for providing an electronic user interface that includes a set of multiple electronic control switches selectable by a user, where the electronic user interface can adjust a complexity level of a display of the set of multiple electronic control switches. In some examples, the user monitoring component 1135 is capable of, configured to, or operable to support a means for monitoring the user while the user engages with the electronic user interface to determine an actual interaction rate for the user. In some examples, the display component 1125 is capable of, configured to, or operable to support a means for adjusting the complexity level based on a comparison of the actual interaction rate to an expected interaction rate associated with a current complexity level for the user.

[0323] In some examples, monitoring to determine the actual interaction rate includes computing the actual interaction rate over a rolling window of one or more interaction cycles.

[0324] In some examples, the electronic user interface includes a scanning interface that sweeps through a quantity of electronic control switches before repeating.

[0325] In some examples, adjusting the complexity level includes at least one of increasing or decreasing a quantity of electronic control switches displayed or switching among interface tiers.

[0326] In some examples, to support adjusting the complexity level, the display component 1125 is capable of, configured to, or operable to support a means for changing a hierarchical depth (which may be an example of the complexity level or otherwise relate to setting the complexity level) of the electronic user interface or changing a quantity of menus navigated by the user to reach a target electronic control switch.

[0327] In some examples, the set of multiple electronic control switches are selectable using a neural activity of the user.

[0328] In some examples, to support determining the expected interaction rate, the display component 1125 is capable of, configured to, or operable to support a means for determining a baseline interaction rate during an initial portion of a session or retrieving the baseline interaction rate from a prior session.Attorney Docket No.: SYNC-N-Z054-00-WO

[0329] In some examples, to support determining the expected interaction rate, the user monitoring component 1135 is capable of, configured to, or operable to support a means for updating the expected interaction rate using an exponential moving average based on one or more prior actual interaction rates.

[0330] In some examples, the comparison yields a pacing index. In some examples, adjusting the complexity level includes increasing the complexity level when the pacing index exceeds a first threshold or decreasing the complexity level when the pacing index is below a second threshold.

[0331] In some examples, increasing the complexity level includes adding additional electronic control switches to the display or increasing a density of electronic control switches. In some examples, decreasing the complexity level includes removing electronic control switches from the display or decreasing the density of electronic control switches.

[0332] In some examples, the display component 1125 is capable of, configured to, or operable to support a means for providing a notification to the user that a modified user interface is available prior to adjusting the complexity level.

[0333] In some examples, the user monitoring component 1135 is capable of, configured to, or operable to support a means for receiving a user confirmation prior to adjusting the complexity level.

[0334] In some examples, the display component 1125 is capable of, configured to, or operable to support a means for providing, in response to determining that the actual interaction rate falls below the expected interaction rate by more than a threshold amount, at least one of predictive text or communication assistance on the electronic user interface to reduce a selection burden on the user.

[0335] In some examples, to support providing the predictive text or the communication assistance, the display component 1125 is capable of, configured to, or operable to support a means for displaying one or more predicted word or phrase completions on the electronic user interface based on a prior interaction history of the user.

[0336] In some examples, the display component 1125 is capable of, configured to, or operable to support a means for providing a display on an electronic user interface that includes a base arrangement of electronic control switches and includes a control setting configured to enable an additive display mode, where the electronic user interface can selectively add an additional region or pane including alternative electronic control switches without changing the base arrangement when the additive display mode is enabled. In some examples, the user monitoring component 1135 is capable of, configured to, or operable to support a means for monitoring user interaction with the base arrangement while the additive display mode isAttorney Docket No.: SYNC-N-Z054-00-WOenabled. In some examples, the user monitoring component 1135 is capable of, configured to, or operable to support a means for determining that the base arrangement exceeds a capability of a user based on the user interaction with the base arrangement. In some examples, the display component 1125 is capable of, configured to, or operable to support a means for adding, to the display and in response to determining that the base arrangement exceeds the capability of the user, the additional region or pane including the alternative electronic control switches without changing the base arrangement.

[0337] In some examples, the alternative electronic control switches are simplified electronic control switches relative to the electronic control switches of the base arrangement.

[0338] In some examples, the additive display mode is an agentic mode. In some examples, enabling the additive display mode disables a leveling mode that changes the base arrangement.

[0339] In some examples, the additional region or pane includes an additional row of electronic control switches.

[0340] In some examples, to support determining that the base arrangement exceeds the capability of the user, the user monitoring component 1135 is capable of, configured to, or operable to support a means for determining that the user fails to select a desired electronic control switch within a time threshold or that an error rate associated with selection exceeds an error threshold.

[0341] In some examples, the capability of the user includes an ability level determined based on an electronic testing activity.

[0342] In some examples, the alternative electronic control switches correspond to at least one of a simplified keyboard interface or a binary-choice interface.

[0343] In some examples, the alternative electronic control switches correspond to at least one of a simplified game interface or a media control interface.

[0344] In some examples, the alternative electronic control switches include context-based suggestions determined based on a current screen or application of the electronic user interface. In some examples, the context-based suggestions are generated using a language model.

[0345] In some examples, the user monitoring component 1135 is capable of, configured to, or operable to support a means for storing a user preference for the additive display mode. In some examples, the user monitoring component 1135 is capable of, configured to, or operable to support a means for applying the user preference in a subsequent session, where the electronic user interface can receive a user input to dismiss the additional region or pane after it is added.Attorney Docket No.: SYNC-N-Z054-00-WO

[0346] In some examples, to support determining that the base arrangement exceeds the capability of the user, the user monitoring component 1135 is capable of, configured to, or operable to support a means for operating the electronic user interface as a scanning interface that sequentially highlights a set of multiple the electronic control switches in interaction cycles. In some examples, to support determining that the base arrangement exceeds the capability of the user, the user monitoring component 1135 is capable of, configured to, or operable to support a means for computing, over a rolling window of interaction cycles, a selection strike rate as a ratio of (i) a sum of scoring weights for interaction cycles in which a selection occurred to (ii) a sum of opportunity weights for interaction cycles in the rolling window, where opportunity weights of the sum of opportunity weights are based on a rest factor assigned to non-selected electronic control switches and scoring weights of the sum of scoring weights are based on a bonus factor that increases credit for selections made in longer interaction cycles. In some examples, to support determining that the base arrangement exceeds the capability of the user, the user monitoring component 1135 is capable of, configured to, or operable to support a means for computing a pacing index based on a ratio of the selection strike rate relative to a baseline selection strike rate for the user. In some examples, to support determining that the base arrangement exceeds the capability of the user, the user monitoring component 1135 is capable of, configured to, or operable to support a means for determining that the base arrangement exceeds the capability of the user when the pacing index is below a threshold.

[0347] In some examples, the display component 1125 is capable of, configured to, or operable to support a means for providing a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display among a set of multiple interface tiers including a highest interface tier. In some examples, the user monitoring component 1135 is capable of, configured to, or operable to support a means for determining whether the user is able to interact with the electronic user interface at the highest interface tier across a threshold quantity of sessions. In some examples, the display component 1125 is capable of, configured to, or operable to support a means for generating a graduation indicator in response to determining that the user is able to interact with the electronic user interface at the highest interface tier across the threshold quantity of sessions, where the graduation indicator indicates a recommendation for the user to transition to a non-adapting user interface that operates without complexity adjustment based on an ability level of the user.Attorney Docket No.: SYNC-N-Z054-00-WO

[0348] In some examples, the threshold quantity of sessions includes a predetermined quantity of consecutive sessions in which the user has consistently interacted with the electronic user interface at the highest interface tier.

[0349] In some examples, to support determining whether the user has interacted with the electronic user interface at the highest interface tier, the user monitoring component 1135 is capable of, configured to, or operable to support a means for determining that at least one of a response time, an accuracy, a reproducibility of the neural activity, or an error rate associated with interaction at the highest interface tier meets or exceeds a performance threshold across the threshold quantity of sessions.

[0350] In some examples, the display component 1125 is capable of, configured to, or operable to support a means for transmitting the graduation indicator to at least one of a caregiver or a clinician associated with the user.

[0351] In some examples, the set of multiple interface tiers includes at least a binarychoice interface tier, a keyboard interface tier, and the highest interface tier. In some examples, the highest interface tier corresponds to a full-complexity interface.

[0352] In some examples, the user monitoring component 1135 is capable of, configured to, or operable to support a means for generating a consistency score based on an interaction of the user with the electronic user interface at the highest interface tier across a set of multiple sessions, where generating the graduation indicator is triggered when the consistency score exceeds a graduation threshold.

[0353] In some examples, the graduation indicator includes at least one of a visual notification displayed on the electronic user interface or an auditory notification.

[0354] FIG. 12 shows an example of a method 1200 that supports adaptive user interfaces for brain-computer interface systems in accordance with one or more aspects of the present disclosure. Operations of the method 1200 may be performed by a processing device 1000 or an adaptive user interface device 1120, or respective components thereof (such as using a processing system 1005 configured to cause the respective device to perform one or more of the operations), as described herein with reference to FIG.s 10 and 11. For example, operations of the method 1200 may be performed by a display component 1125, a user testing component 1130, a user monitoring component 1135, or any combination thereof.

[0355] At 1205, the method may include providing a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display. In some examples, aspects of the operations of 1205 may be performed by a display component 1125.Attorney Docket No.: SYNC-N-Z054-00-WO

[0356] At 1210, the method may include providing an electronic testing activity for the neural activity on the electronic user interface. In some examples, aspects of the operations of 1210 may be performed by a user testing component 1130.

[0357] At 1215, the method may include adjusting the complexity level of the display based on a result of the electronic testing activity. In some examples, aspects of the operations of 1215 may be performed by a display component 1125.

[0358] The method 1200 provides an improvement to the functioning of electronic user interfaces for BCI systems. By replacing subjective, caregiver-dependent interface configuration with an automated, quantitative evaluation of a user’s neural interaction performance, the method 1200 improves the ability of the electronic user interface itself to serve users with neurological disabilities (a result that generic, non-adaptive user interfaces cannot achieve). The adjustment of the complexity level based on the result of the electronic testing activity may include a structural reconfiguration of the electronic control switches displayed on the electronic user interface.

[0359] FIG. 13 shows an example of a method 1300 that supports adaptive user interfaces for brain-computer interface systems in accordance with one or more aspects of the present disclosure. Operations of the method 1300 may be performed by a processing device 1000 or an adaptive user interface device 1120, or respective components thereof (such as using a processing system 1005 configured to cause the respective device to perform one or more of the operations), as described herein with reference to FIG.s 10 and 11. For example, operations of the method 1300 may be performed by a display component 1125, a user testing component 1130, a user monitoring component 1135, or any combination thereof.

[0360] At 1305, the method may include providing a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display. In some examples, aspects of the operations of 1305 may be performed by a display component 1125.

[0361] At 1310, the method may include monitoring the user while engaging the electronic user interface to determine an ability level of the user to interact with the electronic user interface using the neural activity. In some examples, aspects of the operations of 1310 may be performed by a user monitoring component 1135.

[0362] At 1315, the method may include adjusting the complexity level of the set of multiple electronic control switches displayed by the electronic user interface based on the ability level of the user. In some examples, aspects of the operations of 1315 may be performed by a display component 1125.Attorney Docket No.: SYNC-N-Z054-00-WO

[0363] The method 1300 provides an improvement to assistive technology user interfaces by enabling the electronic user interface to continuously and autonomously track a user’s neurological capability in real time and reconfigure its structural layout accordingly, without (or with reduced) manual intervention by a caregiver or clinician. This continuous, automated self-calibration may be part of the architecture of the BCI system (including the neural interface device, the processing system, and the electronic user interface) and may provide improvement in the user’s ability to interact with electronic devices, reducing fatigue, frustration, and caregiver dependency in a manner that static or manually configured interfaces cannot provide.

[0364] FIG. 14 shows an example of a method 1400 that supports adaptive user interfaces for brain-computer interface systems in accordance with one or more aspects of the present disclosure. Operations of the method 1400 may be performed by a processing device 1000 or an adaptive user interface device 1120, or respective components thereof (such as using a processing system 1005 configured to cause the respective device to perform one or more of the operations), as described herein with reference to FIG.s 10 and 11. For example, operations of the method 1400 may be performed by a display component 1125, a user testing component 1130, a user monitoring component 1135, or any combination thereof.

[0365] At 1405, the method may include providing an electronic user interface for interacting with an electronic device using a set of multiple electronic control switches displayed by the electronic user interface, where the electronic user interface can adjust a complexity level of a display of one or more of the set of multiple electronic control switches. In some examples, aspects of the operations of 1405 may be performed by a display component 1125.

[0366] At 1410, the method may include monitoring a parameter associated with a user when the user engages the electronic user interface. In some examples, aspects of the operations of 1410 may be performed by a user monitoring component 1135.

[0367] At 1415, the method may include adjusting the complexity level of the set of multiple electronic control switches displayed based on the parameter associated with the user. In some examples, aspects of the operations of 1415 may be performed by a display component 1125.

[0368] The method 1400 provides parameter monitoring to the structural configuration of an electronic user interface, providing an improvement in the accessibility and usability of assistive technology across a wide range of users, input modalities, and use contexts. The adjustment of the complexity level of the electronic control switches based on the monitored parameter includes changes to the display presented to the user and enables a single adaptiveAttorney Docket No.: SYNC-N-Z054-00-WOuser interface implementation to serve users across diverse assistive technology configurations without separate system implementations for each input modality or use context.

[0369] FIG. 15 shows an example of a method 1500 that supports adaptive user interfaces for brain-computer interface systems in accordance with one or more aspects of the present disclosure. Operations of the method 1500 may be performed by a processing device 1000 or an adaptive user interface device 1120, or respective components thereof (such as using a processing system 1005 configured to cause the respective device to perform one or more of the operations), as described herein with reference to FIG.s 10 and 11. For example, operations of the method 1500 may be performed by a display component 1125, a user testing component 1130, a user monitoring component 1135, or any combination thereof.

[0370] At 1505, the method may include providing an electronic user interface that includes a set of multiple electronic control switches and a navigation tool for guiding navigation among the set of multiple electronic control switches. In some examples, aspects of the operations of 1505 may be performed by a display component 1125.

[0371] At 1510, the method may include determining a traversal level for at least one electronic control switch based on an amount of time for a user to navigate to the at least one electronic control switch using the navigation tool. In some examples, aspects of the operations of 1510 may be performed by a user monitoring component 1135.

[0372] At 1515, the method may include determining a selection level for the at least one electronic control switch based on a quantity of instances of a selection input by the user to select the at least one electronic control switch. In some examples, aspects of the operations of 1515 may be performed by a user monitoring component 1135.

[0373] At 1520, the method may include adjusting the electronic user interface to be associated with a complexity level that is based on the traversal level and the selection level. In some examples, aspects of the operations of 1520 may be performed by a display component 1125.

[0374] The method 1500 provides an improvement to interface complexity assessment by independently capturing two distinct dimensions of interaction difficulty, including the navigational burden of reaching an electronic control switch (the traversal level) and the selection burden of activating it (the selection level), and combining these dimensions into a single, quantitative complexity level that drives the structural configuration of the electronic user interface. This two-dimensional characterization enables the BCI system to configure the electronic user interface in a manner specifically tailored to each user’s individual profile of neurological strengths and limitations, a level of personalization that single-dimensionalAttorney Docket No.: SYNC-N-Z054-00-WOmetrics such as throughput might not be able to support, and that produces an improvement in the user’s ability to interact with the BCI system.

[0375] FIG. 16 shows an example of a method 1600 that supports adaptive user interfaces for brain-computer interface systems in accordance with one or more aspects of the present disclosure. Operations of the method 1600 may be performed by a processing device 1000 or an adaptive user interface device 1120, or respective components thereof (such as using a processing system 1005 configured to cause the respective device to perform one or more of the operations), as described herein with reference to FIG.s 10 and 11. For example, operations of the method 1600 may be performed by a display component 1125, a user testing component 1130, a user monitoring component 1135, or any combination thereof.

[0376] At 1605, the method may include providing an electronic user interface that includes a set of multiple electronic control switches selectable by a user, where the electronic user interface can adjust a complexity level of a display of the set of multiple electronic control switches. In some examples, aspects of the operations of 1605 may be performed by a display component 1125.

[0377] At 1610, the method may include monitoring the user while the user engages with the electronic user interface to determine an actual interaction rate for the user. In some examples, aspects of the operations of 1610 may be performed by a user monitoring component 1135.

[0378] At 1615, the method may include adjusting the complexity level based on a comparison of the actual interaction rate to an expected interaction rate associated with a current complexity level for the user. In some examples, aspects of the operations of 1615 may be performed by a display component 1125.

[0379] The method 1600 provides a (real-time) closed-loop feedback mechanism that (continuously) monitors a user’s actual interaction rate with the electronic user interface and compares it to a personalized expected baseline, producing a quantitative signal that drives structural adjustments to the complexity of the display. This real-time, within-session adaptation may be part of the specific operational architecture of the scanning interface (in which the electronic user interface sequentially highlights electronic control switches in measurable interaction cycles) and may provide an improvement in the user’s ability to maintain effective communication through the BCI system during periods of neurological fatigue or reduced performance, without (or with reduced) intervention by a caregiver or clinician.

[0380] FIG. 17 shows an example of a method 1700 that supports adaptive user interfaces for brain-computer interface systems in accordance with one or more aspects of the presentAttorney Docket No.: SYNC-N-Z054-00-WOdisclosure. Operations of the method 1700 may be performed by a processing device 1000 or an adaptive user interface device 1120, or respective components thereof (such as using a processing system 1005 configured to cause the respective device to perform one or more of the operations), as described herein with reference to FIG.s 10 and 11. For example, operations of the method 1700 may be performed by a display component 1125, a user testing component 1130, a user monitoring component 1135, or any combination thereof.

[0381] At 1705, the method may include providing a display on an electronic user interface that includes a base arrangement of electronic control switches and includes a control setting configured to enable an additive display mode, where the electronic user interface can selectively add an additional region or pane including alternative electronic control switches without changing the base arrangement when the additive display mode is enabled. In some examples, aspects of the operations of 1705 may be performed by a display component 1125.

[0382] At 1710, the method may include monitoring user interaction with the base arrangement while the additive display mode is enabled. In some examples, aspects of the operations of 1710 may be performed by a user monitoring component 1135.

[0383] At 1715, the method may include determining that the base arrangement exceeds a capability of a user based on the user interaction with the base arrangement. In some examples, aspects of the operations of 1715 may be performed by a user monitoring component 1135.

[0384] At 1720, the method may include adding, to the display and in response to determining that the base arrangement exceeds the capability of the user, the additional region or pane including the alternative electronic control switches without changing the base arrangement. In some examples, aspects of the operations of 1720 may be performed by a display component 1125.

[0385] The method 1700 provides an improvement to the electronic user interface by adding a new region or pane of alternative electronic control switches to the display in response to a detected reduction in the user’s interaction capability, without modifying the user’s existing base arrangement. This non-destructive, additive structural modification (which preserves the user’s familiarity with the base interface while simultaneously providing a simplified alternative) includes a reconfiguration of the display that accommodates users (e.g., with neurological disabilities) who may rely on or desire interface familiarity for effective BCI system operation.

[0386] FIG. 18 shows an example of a method 1800 that supports adaptive user interfaces for brain-computer interface systems in accordance with one or more aspects of the present disclosure. Operations of the method 1800 may be performed by a processing device 1000 or an adaptive user interface device 1120, or respective components thereof (such as using aAttorney Docket No.: SYNC-N-Z054-00-WOprocessing system 1005 configured to cause the respective device to perform one or more of the operations), as described herein with reference to FIG.s 10 and 11. For example, operations of the method 1800 may be performed by a display component 1125, a user testing component 1130, a user monitoring component 1135, or any combination thereof.

[0387] At 1805, the method may include providing a display on an electronic user interface operative with the brain-computer interface, where the display includes a set of multiple electronic control switches selectable using a neural activity of a user, and where the electronic user interface can adjust a complexity level of the display among a set of multiple interface tiers including a highest interface tier. In some examples, aspects of the operations of 1805 may be performed by a display component 1125.

[0388] At 1810, the method may include determining whether the user is able to interact with the electronic user interface at the highest interface tier across a threshold quantity of sessions. In some examples, aspects of the operations of 1810 may be performed by a user monitoring component 1135.

[0389] At 1815, the method may include generating a graduation indicator in response to determining that the user is able to interact with the electronic user interface at the highest interface tier across the threshold quantity of sessions, where the graduation indicator indicates a recommendation for the user to transition to a non-adapting user interface that operates without complexity adjustment based on an ability level of the user. In some examples, aspects of the operations of 1815 may be performed by a display component 1125.

[0390] The method 1800 supports an application of multi-session performance tracking to the generation of a system-produced output (the graduation indicator) that determines when a user of a B CI system has achieved sufficient neurological proficiency to transition to a nonadapting (e.g., “standard”) user interface. This graduation indicator may be an automatically generated signal produced by the BCI system upon satisfaction of quantitatively defined performance criteria across a threshold number of sessions, and may be an output that enables BCI users to transition to greater independence (without extensive and / or subjective observation by a caregiver).

[0391] Implementation examples are described in the following numbered clauses:

[0392] Aspect 1 : A method of adapting a brain-computer interface, comprising: providing a display on an electronic user interface operative with the brain-computer interface, wherein the display comprises a plurality of electronic control switches selectable using a neural activity of a user, and wherein the electronic user interface can adjust a complexity level of the display; providing an electronic testing activity for the neural activity on the electronic userAttorney Docket No.: SYNC-N-Z054-00-WOinterface; and adjusting the complexity level of the display based at least in part on a result of the electronic testing activity.

[0393] Aspect 2: The method of aspect 1, further comprising: monitoring the electronic testing activity during engagement by the user, wherein adjusting the complexity level is in accordance with monitoring the electronic testing activity during the engagement by the user.

[0394] Aspect 3: The method of any of aspects 1 through 2, wherein adjusting the complexity level comprises: increasing or decreasing a quantity of the plurality of electronic control switches displayed on the electronic user interface.

[0395] Aspect 4: The method of any of aspects 1 through 3, wherein adjusting the complexity level comprises: changing at least one of a layout, a spacing, a density, a size, a color, a contrast, a text label, an order, or a placement of one or more of the plurality of electronic control switches.

[0396] Aspect 5: The method of any of aspects 1 through 4, wherein adjusting the complexity level comprises: changing at least one of a speed or a path of a navigation tool for the user to navigate among the plurality of electronic control switches.

[0397] Aspect 6: The method of any of aspects 1 through 5, wherein providing the electronic testing activity comprises: prompting the user to select a target electronic control switch displayed on the electronic user interface.

[0398] Aspect 7: The method of aspect 6, wherein prompting the user to select the target electronic control switch comprises: iteratively prompting the user to select additional target electronic control switches having: increased navigation complexity in response to a successful selection of a prior target electronic control switch, or decreased navigation complexity in response to an unsuccessful selection of a prior target electronic control switch.

[0399] Aspect 8: The method of any of aspects 1 through 7, wherein the result of the electronic testing activity comprises at least one of a response time, an accuracy, a reproducibility of the neural activity, or an error rate associated with a selection of one or more target electronic control switches.

[0400] Aspect 9: The method of any of aspects 1 through 8, wherein adjusting the complexity level comprises: selecting, as the plurality of electronic control switches for display, a subset of electronic control switches having complexity levels not exceeding an ability level determined based at least in part on the electronic testing activity.

[0401] Aspect 10: The method of aspect 9, wherein selecting the subset of electronic control switches comprises: selecting the subset of electronic control switches such that a complexity level of the display, computed based at least in part on a maximum, an average, orAttorney Docket No.: SYNC-N-Z054-00-WOa weighted average of complexity levels of electronic control switches in the subset of electronic control switches, does not exceed the ability level.

[0402] Aspect 11 : The method of any of aspects 9 through 10, wherein a complexity level of an electronic control switch is based at least in part on a traversal level and a selection level, the traversal level is based at least in part on an amount of time or a quantity of navigation steps for navigating to the electronic control switch, and the selection level is based at least in part on a quantity of instances of the neural activity to select the electronic control switch.

[0403] Aspect 12: The method of any of aspects 1 through 11, wherein providing the electronic testing activity comprises: initiating the electronic testing activity at least one of upon initial setup of the brain-computer interface, according to a schedule, in response to detected selection errors during non-testing use, or in response to a user selection of a testing command switch.

[0404] Aspect 13: The method of any of aspects 1 through 12, wherein providing the electronic testing activity comprises: using a model to determine which target electronic control switches from a group of target electronic control switches to prompt the user to select.

[0405] Aspect 14: The method of aspect 13, wherein the model uses an input of at least one of prior success or failure in selecting targets, an error rate, a response time, a traversal level, or a selection level, and outputs at least one of a next target electronic control switch or a next navigation complexity.

[0406] Aspect 15: The method of any of aspects 1 through 14, wherein the electronic user interface is configured to adjust the complexity level of the display by increasing or decreasing a navigation complexity for the user to navigate the plurality of electronic control switches displayed by the electronic user interface.

[0407] Aspect 16: The method of any of aspects 1 through 15, wherein the neural activity comprises an endogenous signal representative of neural activity detected by a neural interface device.

[0408] Aspect 17: A method of adapting a brain-computer interface, comprising: providing a display on an electronic user interface operative with the brain-computer interface, wherein the display comprises a plurality of electronic control switches selectable using a neural activity of a user, and wherein the electronic user interface can adjust a complexity level of the display; monitoring the user while engaging the electronic user interface to determine an ability level of the user to interact with the electronic user interface using the neural activity; and adjusting the complexity level of the plurality of electronic control switches displayed by the electronic user interface based at least in part on the ability level of the user.Attorney Docket No.: SYNC-N-Z054-00-WO

[0409] Aspect 18: The method of aspect 17, wherein determining the ability level comprises: determining at least one of a response time for selection of an electronic control switch, an accuracy of selection of an electronic control switch, a reproducibility of neural activity used for selection, or an error rate for selection.

[0410] Aspect 19: The method of any of aspects 17 through 18, wherein the ability level corresponds to a highest complexity level of an electronic control switch that the user is able to reliably select with less than a threshold error rate.

[0411] Aspect 20: The method of any of aspects 17 through 19, wherein determining the ability level comprises: providing an electronic testing activity that prompts selection of one or more target electronic control switches having different navigation complexities; and determining the ability level based at least in part on a performance in the electronic testing activity.

[0412] Aspect 21 : The method of aspect 20, wherein determining the ability level comprises: determining a numerical level score based at least in part on a combination of (i) a quantity of navigation steps to reach each of the one or more target electronic control switches, and (ii) a quantity of selection inputs to select each of the one or more target electronic control switches.

[0413] Aspect 22: The method of any of aspects 17 through 21, wherein adjusting the complexity level comprises: displaying a subset of the plurality of electronic control switches that excludes electronic control switches having complexity levels exceeding the ability level.

[0414] Aspect 23: The method of any of aspects 17 through 22, wherein the electronic user interface comprises a keyboard interface, and adjusting the complexity level comprises selecting a keyboard layout from a set of keyboard layouts comprising at least two of a QWERTY keyboard, an ABC keyboard, an ABC tiered keyboard, or a vowel-based keyboard.

[0415] Aspect 24: The method of any of aspects 17 through 23, wherein adjusting the complexity level comprises: transitioning the electronic user interface among interface tiers that comprise at least a binary-choice interface tier and a keyboard interface tier.

[0416] Aspect 25: The method of aspect 24, wherein transitioning among the interface tiers comprises displaying a binary-choice board comprising “yes” and “no” at a first tier of the interface tiers and displaying a full keyboard at a second tier of the interface tiers.

[0417] Aspect 26: The method of aspect 25, further comprising: removing the binarychoice board from the display when the second tier is displayed.

[0418] Aspect 27: The method of any of aspects 17 through 26, wherein adjusting the complexity level comprises: changing an order or placement of an electronic control switch onAttorney Docket No.: SYNC-N-Z054-00-WOthe electronic user interface based at least in part on a frequency of selection of the electronic control switch.

[0419] Aspect 28: The method of any of aspects 17 through 27, wherein adjusting the complexity level comprises: changing at least one of a start position or a path of a navigation tool for the user to navigate among the plurality of electronic control switches based at least in part on a frequency of selection of one or more electronic control switches.

[0420] Aspect 29: The method of any of aspects 17 through 28, wherein adjusting the complexity level comprises: changing an algorithm used to process signals representative of the neural activity of the user to allow selection of an electronic control switch with more precise or less precise signals.

[0421] Aspect 30: The method of any of aspects 17 through 29, wherein adjusting the complexity level comprises: changing an algorithm that maps the neural activity to selection of the plurality of electronic control switches based at least in part on the ability level.

[0422] Aspect 31: The method of any of aspects 17 through 30, wherein adjusting the complexity level is performed automatically without caregiver intervention, the method further comprising: limiting an adjustment of the complexity level based at least in part on a maximum complexity level.

[0423] Aspect 32: The method of any of aspects 17 through 31, wherein the ability level comprises a literacy score derived from at least one of a response time, an accuracy, a reproducibility of the neural activity, or an error rate associated with interaction with the electronic user interface across a plurality of sessions.

[0424] Aspect 33: The method of aspect 32, wherein the literacy score comprises a braincomputer interface (BCI) literacy score.

[0425] Aspect 34: The method of any of aspects 17 through 33, wherein adjusting the complexity level comprises: unlocking one or more interface capabilities of the electronic user interface in response to the ability level meeting or exceeding a literacy score threshold.

[0426] Aspect 35: The method of any of aspects 17 through 34, wherein monitoring the user comprises: monitoring the user while the user performs one or more activities of daily living using the electronic user interface, wherein the ability level is derived at least in part from a performance of the user during the one or more activities of daily living.

[0427] Aspect 36: The method of any of aspects 17 through 35, wherein the electronic user interface comprises a game interface, and wherein adjusting the complexity level comprises: modifying a structure of the game interface based at least in part on the ability level of the user.

[0428] Aspect 37: The method of aspect 36, wherein modifying the structure of the game interface comprises: replacing a full-input game control interface with a tiered input interfaceAttorney Docket No.: SYNC-N-Z054-00-WOcomprising a reduced set of electronic control switches corresponding to game actions available at the ability level of the user.

[0429] Aspect 38: The method of any of aspects 17 through 37, wherein adjusting the complexity level comprises: generating one or more predictive control suggestions for display on the electronic user interface based at least in part on the ability level of the user and a predicted next interaction of the user with the electronic user interface.

[0430] Aspect 39: The method of any of aspects 17 through 38, wherein adjusting the complexity level comprises: generating a set of electronic control switches for display on the electronic user interface using a language model, wherein the set of electronic control switches is generated based at least in part on a current application or screen associated with the electronic user interface.

[0431] Aspect 40: A method of adapting an interface, comprising: providing an electronic user interface for interacting with an electronic device using a plurality of electronic control switches displayed by the electronic user interface, wherein the electronic user interface can adjust a complexity level of a display of one or more of the plurality of electronic control switches; monitoring a parameter associated with a user when the user engages the electronic user interface; and adjusting the complexity level of the plurality of electronic control switches displayed based at least in part on the parameter associated with the user.

[0432] Aspect 41 : The method of aspect 40, wherein the parameter associated with the user comprises a physiological parameter selected from a heart rate, a body temperature, a blood pressure, a breathing rate, or a pupil dilation.

[0433] Aspect 42: The method of any of aspects 40 through 41, wherein the parameter associated with the user comprises a location of the user, and adjusting the complexity level comprises presenting control switches associated with a location-specific task.

[0434] Aspect 43: The method of any of aspects 40 through 42, wherein the parameter associated with the user comprises a time of day, and adjusting the complexity level comprises decreasing the complexity level at nighttime.

[0435] Aspect 44: The method of any of aspects 40 through 43, wherein the parameter associated with the user comprises at least one of an error rate or a response time associated with selection of the plurality of electronic control switches during non-testing use.

[0436] Aspect 45: The method of any of aspects 40 through 44, wherein the parameter associated with the user comprises a use history indicating a frequency of selection of one or more electronic control switches, and adjusting the complexity level comprises relocating at least one of the one or more electronic control switches.Attorney Docket No.: SYNC-N-Z054-00-WO

[0437] Aspect 46: The method of any of aspects 40 through 45, wherein the parameter associated with the user comprises an ability level of the user to interact with the electronic user interface.

[0438] Aspect 47: The method of any of aspects 40 through 46, wherein monitoring the parameter associated with the user comprises receiving the parameter from at least one of an external device, a personal electronic device, or a remote server.

[0439] Aspect 48: The method of any of aspects 40 through 47, wherein adjusting the complexity level is based at least in part on aggregating a plurality of parameters associated with the user to determine the complexity level.

[0440] Aspect 49: The method of any of aspects 40 through 48, wherein the electronic user interface can operate with a brain-computer interface, and each of the plurality of electronic control switches is selectable using a neural activity of the user.

[0441] Aspect 50: The method of any of aspects 40 through 49, wherein the parameter associated with the user comprises a brain-computer interface literacy score derived from at least one of a response time, an accuracy, a reproducibility of a neural activity, or an error rate associated with interaction with the electronic user interface across a plurality of sessions.

[0442] Aspect 51 : The method of any of aspects 40 through 50, wherein adjusting the complexity level comprises: unlocking one or more interface capabilities of the electronic user interface in response to the parameter meeting or exceeding a literacy threshold.

[0443] Aspect 52: The method of any of aspects 40 through 51, wherein monitoring the parameter associated with the user comprises: monitoring the user while performing one or more activities of daily living using the electronic user interface, wherein the parameter is derived at least in part from a performance of the user during the one or more activities of daily living.

[0444] Aspect 53: The method of any of aspects 40 through 52, wherein the electronic user interface comprises a game interface, and wherein adjusting the complexity level comprises: modifying a structure of the game interface based at least in part on the parameter associated with the user.

[0445] Aspect 54: The method of aspect 53, wherein modifying the structure of the game interface comprises: replacing a full-input game control interface with a tiered input interface comprising a reduced set of electronic control switches corresponding to game actions available based on the parameter associated with the user.

[0446] Aspect 55: The method of any of aspects 40 through 54, wherein adjusting the complexity level comprises: generating one or more predictive control suggestions for displayAttorney Docket No.: SYNC-N-Z054-00-WOon the electronic user interface based at least in part on the parameter associated with the user and a predicted next interaction of the user with the electronic user interface.

[0447] Aspect 56: The method of any of aspects 40 through 55, wherein adjusting the complexity level comprises: generating a set of electronic control switches for display on the electronic user interface using a language model, wherein the set of electronic control switches is generated based at least in part on a current application or screen associated with the electronic user interface.

[0448] Aspect 57: A method of adapting a brain-computer interface, comprising: providing an electronic user interface that comprises a plurality of electronic control switches and a navigation tool for guiding navigation among the plurality of electronic control switches; determining a traversal level for at least one electronic control switch based at least in part on an amount of time for a user to navigate to the at least one electronic control switch using the navigation tool; determining a selection level for the at least one electronic control switch based at least in part on a quantity of instances of a selection input by the user to select the at least one electronic control switch; and adjusting the electronic user interface to be associated with a complexity level that is based at least in part on the traversal level and the selection level.

[0449] Aspect 58: The method of aspect 57, further comprising: determining the complexity level for the electronic user interface based at least in part on a combination of the traversal level and the selection level.

[0450] Aspect 59: The method of any of aspects 57 through 58, further comprising: determining the complexity level based at least in part on a maximum complexity level among the plurality of electronic control switches displayed or based at least in part on an average or weighted average of complexity levels of a subset of the plurality of electronic control switches displayed.

[0451] Aspect 60: The method of any of aspects 57 through 59, wherein the navigation tool comprises an indicator, an effector, or a cursor that is displayed on the electronic user interface and that guides navigation among the plurality of electronic control switches.

[0452] Aspect 61 : The method of any of aspects 57 through 60, wherein determining the traversal level comprises: determining a quantity of navigation steps or scan cycles to navigate to the at least one electronic control switch using the navigation tool.

[0453] Aspect 62: The method of any of aspects 57 through 61, wherein the selection input comprises neural activity of the user.Attorney Docket No.: SYNC-N-Z054-00-WO

[0454] Aspect 63: The method of any of aspects 57 through 62, wherein determining the selection level comprises: applying a weight to a selection input type of the selection input based at least in part on a difficulty of engaging in the selection input type.

[0455] Aspect 64: The method of aspect 63, wherein the weight is user specific.

[0456] Aspect 65: The method of any of aspects 57 through 64, wherein adjusting the electronic user interface comprises: selecting a subset of electronic control switches for display based at least in part on a rank or level assigned to each electronic control switch, wherein the rank or level is set by at least one of the user, a caregiver, or the electronic user interface.

[0457] Aspect 66: The method of any of aspects 57 through 65, further comprising: determining the traversal level and the selection level during an electronic testing activity that prompts selection of one or more target electronic control switches.

[0458] Aspect 67: The method of aspect 66, wherein the electronic testing activity comprises a single-switch scanner test or a multi-action scanner test that uses different forms of neural activity to access different rows, columns, or subsets of electronic control switches.

[0459] Aspect 68: The method of any of aspects 57 through 67, wherein adjusting the electronic user interface comprises: transitioning among interface tiers comprising a binarychoice interface tier and a keyboard interface tier, comprising selecting a keyboard layout from a set of keyboard layouts comprising at least two of a QWERTY keyboard, an ABC keyboard, an ABC tiered keyboard, or a vowel-based keyboard.

[0460] Aspect 69: A method of adapting a brain-computer interface, comprising: providing an electronic user interface that comprises a plurality of electronic control switches selectable by a user, wherein the electronic user interface can adjust a complexity level of a display of the plurality of electronic control switches; monitoring the user while the user engages with the electronic user interface to determine an actual interaction rate for the user; and adjusting the complexity level based at least in part on a comparison of the actual interaction rate to an expected interaction rate associated with a current complexity level for the user.

[0461] Aspect 70: The method of aspect 69, wherein monitoring to determine the actual interaction rate comprises computing the actual interaction rate over a rolling window of one or more interaction cycles.

[0462] Aspect 71 : The method of any of aspects 69 through 70, wherein the electronic user interface comprises a scanning interface that sweeps through a quantity of electronic control switches before repeating.

[0463] Aspect 72: The method of any of aspects 69 through 71, wherein adjusting the complexity level comprises at least one of increasing or decreasing a quantity of electronic control switches displayed or switching among interface tiers.Attorney Docket No.: SYNC-N-Z054-00-WO

[0464] Aspect 73: The method of any of aspects 69 through 72, wherein adjusting the complexity level comprises: changing a hierarchical depth of the electronic user interface or changing a quantity of menus navigated by the user to reach a target electronic control switch.

[0465] Aspect 74: The method of any of aspects 69 through 73, wherein the plurality of electronic control switches are selectable using a neural activity of the user.

[0466] Aspect 75: The method of any of aspects 69 through 74, wherein determining the expected interaction rate comprises: determining a baseline interaction rate during an initial portion of a session or retrieving the baseline interaction rate from a prior session.

[0467] Aspect 76: The method of any of aspects 69 through 75, wherein determining the expected interaction rate comprises: updating the expected interaction rate using an exponential moving average based at least in part on one or more prior actual interaction rates.

[0468] Aspect 77: The method of any of aspects 69 through 76, wherein the comparison yields a pacing index, and adjusting the complexity level comprises increasing the complexity level when the pacing index exceeds a first thr...

Claims

Attorney Docket No.: SYNC-N-Z054-00-WOCLAIMSWhat is claimed is:

1. A method of adapting a brain-computer interface, comprising: providing a display on an electronic user interface operative with the brain-computer interface, wherein the display comprises a plurality of electronic control switches selectable using a neural activity of a user, and wherein the electronic user interface can adjust a complexity level of the display;providing an electronic testing activity for the neural activity on the electronic user interface; andadjusting the complexity level of the display based at least in part on a result of the electronic testing activity.

2. The method of claim 1, further comprising:monitoring the electronic testing activity during engagement by the user, wherein adjusting the complexity level is in accordance with monitoring the electronic testing activity during the engagement by the user.

3. The method of any of claims 1 through 2, wherein adjusting the complexity level comprises increasing or decreasing a quantity of the plurality of electronic control switches displayed on the electronic user interface.

4. The method of any of claims 1 through 3, wherein adjusting the complexity level comprises changing at least one of a layout, a spacing, a density, a size, a color, a contrast, a text label, an order, or a placement of one or more of the plurality of electronic control switches.

5. The method of any of claims 1 through 4, wherein adjusting the complexity level comprises changing at least one of a speed or a path of a navigation tool for the user to navigate among the plurality of electronic control switches.

6. The method of any of claims 1 through 5, wherein providing the electronic testing activity comprises prompting the user to select a target electronic control switch displayed on the electronic user interface.

7. The method of claim 6, wherein prompting the user to select the target electronic control switch comprises:iteratively prompting the user to select additional target electronic control switches having:increased navigation complexity in response to a successful selection of a prior target electronic control switch, orAttorney Docket No.: SYNC-N-Z054-00-WOdecreased navigation complexity in response to an unsuccessful selection of a prior target electronic control switch.

8. The method of any of claims 1 through 7, wherein the result of the electronic testing activity comprises at least one of a response time, an accuracy, a reproducibility of the neural activity, or an error rate associated with a selection of one or more target electronic control switches.

9. The method of any of claims 1 through 8, wherein adjusting the complexity level comprises selecting, as the plurality of electronic control switches for display, a subset of electronic control switches having complexity levels not exceeding an ability level determined based at least in part on the electronic testing activity.

10. The method of claim 9, wherein selecting the subset of electronic control switches comprises:selecting the subset of electronic control switches such that a complexity level of the display, computed based at least in part on a maximum, an average, or a weighted average of complexity levels of electronic control switches in the subset of electronic control switches, does not exceed the ability level.

11. The method of any of claims 9 through 10, wherein:a complexity level of an electronic control switch is based at least in part on a traversal level and a selection level,the traversal level is based at least in part on an amount of time or a quantity of navigation steps for navigating to the electronic control switch, andthe selection level is based at least in part on a quantity of instances of the neural activity to select the electronic control switch.

12. The method of any of claims 1 through 11, wherein providing the electronic testing activity comprises initiating the electronic testing activity at least one of upon initial setup of the brain-computer interface, according to a schedule, in response to detected selection errors during non-testing use, or in response to a user selection of a testing command switch.

13. The method of any of claims 1 through 12, wherein providing the electronic testing activity comprises using a model to determine which target electronic control switches from a group of target electronic control switches to prompt the user to select.

14. The method of claim 13, wherein the model uses an input of at least one of prior success or failure in selecting targets, an error rate, a response time, a traversal level, or a selection level, and outputs at least one of a next target electronic control switch or a next navigation complexity.Attorney Docket No.: SYNC-N-Z054-00-WO15. The method of any of claims 1 through 14, wherein the electronic user interface is configured to adjust the complexity level of the display by increasing or decreasing a navigation complexity for the user to navigate the plurality of electronic control switches displayed by the electronic user interface.

16. The method of any of claims 1 through 15, wherein the neural activity comprises an endogenous signal representative of neural activity detected by a neural interface device.

17. A method of adapting a brain-computer interface, comprising:providing a display on an electronic user interface operative with the brain-computer interface, wherein the display comprises a plurality of electronic control switches selectable using a neural activity of a user, and wherein the electronic user interface can adjust a complexity level of the display;monitoring the user while engaging the electronic user interface to determine an ability level of the user to interact with the electronic user interface using the neural activity; and adjusting the complexity level of the plurality of electronic control switches displayed by the electronic user interface based at least in part on the ability level of the user.

18. The method of claim 17, wherein determining the ability level comprises: determining at least one of a response time for selection of an electronic control switch, an accuracy of selection of an electronic control switch, a reproducibility of neural activity used for selection, or an error rate for selection.

19. The method of any of claims 17 through 18, wherein the ability level corresponds to a highest complexity level of an electronic control switch that the user is able to reliably select with less than a threshold error rate.

20. The method of any of claims 17 through 19, wherein determining the ability level comprises:providing an electronic testing activity that prompts selection of one or more target electronic control switches having different navigation complexities; anddetermining the ability level based at least in part on a performance in the electronic testing activity.

21. The method of claim 20, wherein determining the ability level comprises: determining a numerical level score based at least in part on a combination of (i) a quantity of navigation steps to reach each of the one or more target electronic control switches, and (ii) a quantity of selection inputs to select each of the one or more target electronic control switches.Attorney Docket No.: SYNC-N-Z054-00-WO22. The method of any of claims 17 through 21, wherein adjusting the complexity level comprises displaying a subset of the plurality of electronic control switches that excludes electronic control switches having complexity levels exceeding the ability level.

23. The method of any of claims 17 through 22, wherein:the electronic user interface comprises a keyboard interface, andadjusting the complexity level comprises selecting a keyboard layout from a set of keyboard layouts comprising at least two of a QWERTY keyboard, an ABC keyboard, an ABC tiered keyboard, or a vowel-based keyboard.

24. The method of any of claims 17 through 23, wherein adjusting the complexity level comprises transitioning the electronic user interface among interface tiers that comprise at least a binary-choice interface tier and a keyboard interface tier.

25. The method of claim 24, wherein transitioning among the interface tiers comprises displaying a binary-choice board comprising “yes” and “no” at a first tier of the interface tiers and displaying a full keyboard at a second tier of the interface tiers.

26. The method of claim 25, further comprising:removing the binary-choice board from the display when the second tier is displayed.

27. The method of any of claims 17 through 26, wherein adjusting the complexity level comprises changing an order or placement of an electronic control switch on the electronic user interface based at least in part on a frequency of selection of the electronic control switch.

28. The method of any of claims 17 through 27, wherein adjusting the complexity level comprises changing at least one of a start position or a path of a navigation tool for the user to navigate among the plurality of electronic control switches based at least in part on a frequency of selection of one or more electronic control switches.

29. The method of any of claims 17 through 28, wherein adjusting the complexity level comprises changing an algorithm used to process signals representative of the neural activity of the user to allow selection of an electronic control switch with more precise or less precise signals.

30. The method of any of claims 17 through 29, wherein adjusting the complexity level comprises changing an algorithm that maps the neural activity to selection of the plurality of electronic control switches based at least in part on the ability level.

31. The method of any of claims 17 through 30, wherein adjusting the complexity level is performed automatically without caregiver intervention, the method further comprising:limiting an adjustment of the complexity level based at least in part on a maximum complexity level.Attorney Docket No.: SYNC-N-Z054-00-WO32. The method of any of claims 17 through 31, wherein the ability level comprises a literacy score derived from at least one of a response time, an accuracy, a reproducibility of the neural activity, or an error rate associated with interaction with the electronic user interface across a plurality of sessions.

33. The method of claim 32, wherein the literacy score comprises a brain-computer interface (BCI) literacy score.

34. The method of any of claims 17 through 33, wherein adjusting the complexity level comprises unlocking one or more interface capabilities of the electronic user interface in response to the ability level meeting or exceeding a literacy score threshold.

35. The method of any of claims 17 through 34, wherein monitoring the user comprises monitoring the user while the user performs one or more activities of daily living using the electronic user interface, wherein the ability level is derived at least in part from a performance of the user during the one or more activities of daily living.

36. The method of any of claims 17 through 35, wherein the electronic user interface comprises a game interface, and wherein adjusting the complexity level comprises modifying a structure of the game interface based at least in part on the ability level of the user.

37. The method of claim 36, wherein modifying the structure of the game interface comprises:replacing a full-input game control interface with a tiered input interface comprising a reduced set of electronic control switches corresponding to game actions available at the ability level of the user.

38. The method of any of claims 17 through 37, wherein adjusting the complexity level comprises generating one or more predictive control suggestions for display on the electronic user interface based at least in part on the ability level of the user and a predicted next interaction of the user with the electronic user interface.

39. The method of any of claims 17 through 38, wherein adjusting the complexity level comprises generating a set of electronic control switches for display on the electronic user interface using a language model, wherein the set of electronic control switches is generated based at least in part on a current application or screen associated with the electronic user interface.

40. A method of adapting an interface, comprising:providing an electronic user interface for interacting with an electronic device using a plurality of electronic control switches displayed by the electronic user interface, wherein the electronic user interface can adjust a complexity level of a display of one or more of the plurality of electronic control switches;Attorney Docket No.: SYNC-N-Z054-00-WOmonitoring a parameter associated with a user when the user engages the electronic user interface; andadjusting the complexity level of the plurality of electronic control switches displayed based at least in part on the parameter associated with the user.

41. The method of claim 40, wherein the parameter associated with the user comprises a physiological parameter selected from a heart rate, a body temperature, a blood pressure, a breathing rate, or a pupil dilation.

42. The method of any of claims 40 through 41, wherein:the parameter associated with the user comprises a location of the user, and adjusting the complexity level comprises presenting control switches associated with a location-specific task.

43. The method of any of claims 40 through 42, wherein:the parameter associated with the user comprises a time of day, andadjusting the complexity level comprises decreasing the complexity level at nighttime.

44. The method of any of claims 40 through 43, wherein the parameter associated with the user comprises at least one of an error rate or a response time associated with selection of the plurality of electronic control switches during non-testing use.

45. The method of any of claims 40 through 44, wherein:the parameter associated with the user comprises a use history indicating a frequency of selection of one or more electronic control switches, andadjusting the complexity level comprises relocating at least one of the one or more electronic control switches.

46. The method of any of claims 40 through 45, wherein the parameter associated with the user comprises an ability level of the user to interact with the electronic user interface.

47. The method of any of claims 40 through 46, wherein monitoring the parameter associated with the user comprises receiving the parameter from at least one of an external device, a personal electronic device, or a remote server.

48. The method of any of claims 40 through 47, wherein adjusting the complexity level is based at least in part on aggregating a plurality of parameters associated with the user to determine the complexity level.

49. The method of any of claims 40 through 48, wherein:the electronic user interface can operate with a brain-computer interface, and each of the plurality of electronic control switches is selectable using a neural activity of the user.Attorney Docket No.: SYNC-N-Z054-00-WO50. The method of any of claims 40 through 49, wherein the parameter associated with the user comprises a brain-computer interface literacy score derived from at least one of a response time, an accuracy, a reproducibility of a neural activity, or an error rate associated with interaction with the electronic user interface across a plurality of sessions.

51. The method of any of claims 40 through 50, wherein adjusting the complexity level comprises unlocking one or more interface capabilities of the electronic user interface in response to the parameter meeting or exceeding a literacy threshold.

52. The method of any of claims 40 through 51, wherein monitoring the parameter associated with the user comprises monitoring the user while performing one or more activities of daily living using the electronic user interface, wherein the parameter is derived at least in part from a performance of the user during the one or more activities of daily living.

53. The method of any of claims 40 through 52, wherein the electronic user interface comprises a game interface, and wherein adjusting the complexity level comprises modifying a structure of the game interface based at least in part on the parameter associated with the user.

54. The method of claim 53, wherein modifying the structure of the game interface comprises:replacing a full-input game control interface with a tiered input interface comprising a reduced set of electronic control switches corresponding to game actions available based on the parameter associated with the user.

55. The method of any of claims 40 through 54, wherein adjusting the complexity level comprises generating one or more predictive control suggestions for display on the electronic user interface based at least in part on the parameter associated with the user and a predicted next interaction of the user with the electronic user interface.

56. The method of any of claims 40 through 55, wherein adjusting the complexity level comprises generating a set of electronic control switches for display on the electronic user interface using a language model, wherein the set of electronic control switches is generated based at least in part on a current application or screen associated with the electronic user interface.

57. A method of adapting a brain-computer interface, comprising:providing an electronic user interface that comprises a plurality of electronic control switches and a navigation tool for guiding navigation among the plurality of electronic control switches;Attorney Docket No.: SYNC-N-Z054-00-WOdetermining a traversal level for at least one electronic control switch based at least in part on an amount of time for a user to navigate to the at least one electronic control switch using the navigation tool;determining a selection level for the at least one electronic control switch based at least in part on a quantity of instances of a selection input by the user to select the at least one electronic control switch; andadjusting the electronic user interface to be associated with a complexity level that is based at least in part on the traversal level and the selection level.

58. The method of claim 57, further comprising:determining the complexity level for the electronic user interface based at least in part on a combination of the traversal level and the selection level.

59. The method of any of claims 57 through 58, further comprising: determining the complexity level based at least in part on a maximum complexity level among the plurality of electronic control switches displayed or based at least in part on an average or weighted average of complexity levels of a subset of the plurality of electronic control switches displayed.

60. The method of any of claims 57 through 59, wherein the navigation tool comprises an indicator, an effector, or a cursor that is displayed on the electronic user interface and that guides navigation among the plurality of electronic control switches.

61. The method of any of claims 57 through 60, wherein determining the traversal level comprises determining a quantity of navigation steps or scan cycles to navigate to the at least one electronic control switch using the navigation tool.

62. The method of any of claims 57 through 61, wherein the selection input comprises neural activity of the user.

63. The method of any of claims 57 through 62, wherein determining the selection level comprises applying a weight to a selection input type of the selection input based at least in part on a difficulty of engaging in the selection input type.

64. The method of claim 63, wherein the weight is user specific.

65. The method of any of claims 57 through 64, wherein adjusting the electronic user interface comprises selecting a subset of electronic control switches for display based at least in part on a rank or level assigned to each electronic control switch, wherein the rank or level is set by at least one of the user, a caregiver, or the electronic user interface.

66. The method of any of claims 57 through 65, further comprising: determining the traversal level and the selection level during an electronic testing activity that prompts selection of one or more target electronic control switches.Attorney Docket No.: SYNC-N-Z054-00-WO67. The method of claim 66, wherein the electronic testing activity comprises a single-switch scanner test or a multi-action scanner test that uses different forms of neural activity to access different rows, columns, or subsets of electronic control switches.

68. The method of any of claims 57 through 67, wherein adjusting the electronic user interface comprises transitioning among interface tiers comprising a binary-choice interface tier and a keyboard interface tier, comprising selecting a keyboard layout from a set of keyboard layouts comprising at least two of a QWERTY keyboard, an ABC keyboard, an ABC tiered keyboard, or a vowel-based keyboard.

69. A method of adapting a brain-computer interface, comprising:providing an electronic user interface that comprises a plurality of electronic control switches selectable by a user, wherein the electronic user interface can adjust a complexity level of a display of the plurality of electronic control switches;monitoring the user while the user engages with the electronic user interface to determine an actual interaction rate for the user; andadjusting the complexity level based at least in part on a comparison of the actual interaction rate to an expected interaction rate associated with a current complexity level for the user.

70. The method of claim 69, wherein monitoring to determine the actual interaction rate comprises computing the actual interaction rate over a rolling window of one or more interaction cycles.

71. The method of any of claims 69 through 70, wherein the electronic user interface comprises a scanning interface that sweeps through a quantity of electronic control switches before repeating.

72. The method of any of claims 69 through 71, wherein adjusting the complexity level comprises at least one of increasing or decreasing a quantity of electronic control switches displayed or switching among interface tiers.

73. The method of any of claims 69 through 72, wherein adjusting the complexity level comprises changing a hierarchical depth of the electronic user interface or changing a quantity of menus navigated by the user to reach a target electronic control switch.

74. The method of any of claims 69 through 73, wherein the plurality of electronic control switches are selectable using a neural activity of the user.

75. The method of any of claims 69 through 74, wherein determining the expected interaction rate comprises determining a baseline interaction rate during an initial portion of a session or retrieving the baseline interaction rate from a prior session.Attorney Docket No.: SYNC-N-Z054-00-WO76. The method of any of claims 69 through 75, wherein determining the expected interaction rate comprises updating the expected interaction rate using an exponential moving average based at least in part on one or more prior actual interaction rates.

77. The method of any of claims 69 through 76, wherein:the comparison yields a pacing index, andadjusting the complexity level comprises increasing the complexity level when the pacing index exceeds a first threshold or decreasing the complexity level when the pacing index is below a second threshold.

78. The method of claim 77, wherein:increasing the complexity level comprises adding additional electronic control switches to the display or increasing a density of electronic control switches, anddecreasing the complexity level comprises removing electronic control switches from the display or decreasing the density of electronic control switches.

79. The method of any of claims 69 through 78, further comprising: providing a notification to the user that a modified user interface is available prior to adjusting the complexity level.

80. The method of any of claims 69 through 79, further comprising:receiving a user confirmation prior to adjusting the complexity level.

81. The method of any of claims 69 through 80, further comprising: providing, in response to determining that the actual interaction rate falls below the expected interaction rate by more than a threshold amount, at least one of predictive text or communication assistance on the electronic user interface to reduce a selection burden on the user.

82. The method of claim 81, wherein providing the predictive text or the communication assistance comprises:displaying one or more predicted word or phrase completions on the electronic user interface based at least in part on a prior interaction history of the user.

83. A method of adapting a brain-computer interface, comprising:providing a display on an electronic user interface that comprises a base arrangement of electronic control switches and comprises a control setting configured to enable an additive display mode, wherein the electronic user interface can selectively add an additional region or pane comprising alternative electronic control switches without changing the base arrangement when the additive display mode is enabled;monitoring user interaction with the base arrangement while the additive display mode is enabled;Attorney Docket No.: SYNC-N-Z054-00-WOdetermining that the base arrangement exceeds a capability of a user based at least in part on the user interaction with the base arrangement; andadding, to the display and in response to determining that the base arrangement exceeds the capability of the user, the additional region or pane comprising the alternative electronic control switches without changing the base arrangement.

84. The method of claim 83, wherein the alternative electronic control switches are simplified electronic control switches relative to the electronic control switches of the base arrangement.

85. The method of any of claims 83 through 84, wherein:the additive display mode is an agentic mode, andenabling the additive display mode disables a leveling mode that changes the base arrangement.

86. The method of any of claims 83 through 85, wherein the additional region or pane comprises an additional row of electronic control switches.

87. The method of any of claims 83 through 86, wherein determining that the base arrangement exceeds the capability of the user comprises determining that the user fails to select a desired electronic control switch within a time threshold or that an error rate associated with selection exceeds an error threshold.

88. The method of any of claims 83 through 87, wherein the capability of the user comprises an ability level determined based at least in part on an electronic testing activity.

89. The method of any of claims 83 through 88, wherein the alternative electronic control switches correspond to at least one of a simplified keyboard interface or a binarychoice interface.

90. The method of any of claims 83 through 89, wherein the alternative electronic control switches correspond to at least one of a simplified game interface or a media control interface.

91. The method of any of claims 83 through 90, wherein:the alternative electronic control switches comprise context-based suggestions determined based at least in part on a current screen or application of the electronic user interface, andthe context-based suggestions are generated using a language model.

92. The method of any of claims 83 through 91, further comprising:storing a user preference for the additive display mode; andapplying the user preference in a subsequent session, wherein the electronic user interface can receive a user input to dismiss the additional region or pane after it is added.Attorney Docket No.: SYNC-N-Z054-00-WO93. The method of any of claims 83 through 92, wherein determining that the base arrangement exceeds the capability of the user comprises:operating the electronic user interface as a scanning interface that sequentially highlights a plurality of the electronic control switches in interaction cycles;computing, over a rolling window of interaction cycles, a selection strike rate as a ratio of (i) a sum of scoring weights for interaction cycles in which a selection occurred to (ii) a sum of opportunity weights for interaction cycles in the rolling window, wherein opportunity weights of the sum of opportunity weights are based at least in part on a rest factor assigned to non-selected electronic control switches and scoring weights of the sum of scoring weights are based at least in part on a bonus factor that increases credit for selections made in longer interaction cycles;computing a pacing index based at least in part on a ratio of the selection strike rate relative to a baseline selection strike rate for the user; anddetermining that the base arrangement exceeds the capability of the user when the pacing index is below a threshold.

94. A method of adapting a brain-computer interface, comprising:providing a display on an electronic user interface operative with the brain-computer interface, wherein the display comprises a plurality of electronic control switches selectable using a neural activity of a user, and wherein the electronic user interface can adjust a complexity level of the display among a plurality of interface tiers including a highest interface tier;determining whether the user is able to interact with the electronic user interface at the highest interface tier across a threshold quantity of sessions; andgenerating a graduation indicator in response to determining that the user is able to interact with the electronic user interface at the highest interface tier across the threshold quantity of sessions, wherein the graduation indicator indicates a recommendation for the user to transition to a non-adapting user interface that operates without complexity adjustment based on an ability level of the user.

95. The method of claim 94, wherein the threshold quantity of sessions comprises a predetermined quantity of consecutive sessions in which the user has consistently interacted with the electronic user interface at the highest interface tier.

96. The method of any of claims 94 through 95, wherein determining whether the user has interacted with the electronic user interface at the highest interface tier comprises determining that at least one of a response time, an accuracy, a reproducibility of the neuralAttorney Docket No.: SYNC-N-Z054-00-WOactivity, or an error rate associated with interaction at the highest interface tier meets or exceeds a performance threshold across the threshold quantity of sessions.

97. The method of any of claims 94 through 96, further comprising: transmitting the graduation indicator to at least one of a caregiver or a clinician associated with the user.

98. The method of any of claims 94 through 97, wherein:the plurality of interface tiers comprises at least a binary-choice interface tier, a keyboard interface tier, and the highest interface tier, andthe highest interface tier corresponds to a full-complexity interface.

99. The method of any of claims 94 through 98, further comprising: generating a consistency score based on an interaction of the user with the electronic user interface at the highest interface tier across a plurality of sessions, wherein generating the graduation indicator is triggered when the consistency score exceeds a graduation threshold.

100. The method of any of claims 94 through 99, wherein the graduation indicator comprises at least one of a visual notification displayed on the electronic user interface or an auditory notification.

101. An apparatus, comprising:a processing system that includes processor circuitry and memory circuitry that stores code, the processing system configured to cause the apparatus to:provide a display on an electronic user interface operative with a braincomputer interface, wherein the display comprises a plurality of electronic control switches selectable using a neural activity of a user, and wherein the electronic user interface can adjust a complexity level of the display;provide an electronic testing activity for the neural activity on the electronic user interface; andadjust the complexity level of the display based at least in part on a result of the electronic testing activity.

102. The apparatus of claim 101, wherein the processing system is further configured to cause the apparatus to:monitor the electronic testing activity during engagement by the user, wherein adjusting the complexity level is in accordance with monitoring the electronic testing activity during the engagement by the user.

103. The apparatus of any of claims 101 through 102, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:increase or decrease a quantity of the plurality of electronic control switches displayedAttorney Docket No.: SYNC-N-Z054-00-WOon the electronic user interface.

104. The apparatus of any of claims 101 through 103, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:change at least one of a layout, a spacing, a density, a size, a color, a contrast, a text label, an order, or a placement of one or more of the plurality of electronic control switches.

105. The apparatus of any of claims 101 through 104, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:change at least one of a speed or a path of a navigation tool for the user to navigate among the plurality of electronic control switches.

106. The apparatus of any of claims 101 through 105, wherein, to provide the electronic testing activity, the processing system is configured to cause the apparatus to:prompt the user to select a target electronic control switch displayed on the electronic user interface.

107. The apparatus of claim 106, wherein, to prompt the user to select the target electronic control switch, the processing system is configured to cause the apparatus to:iteratively prompt the user to select additional target electronic control switches having: increased navigation complexity in response to a successful selection of a prior target electronic control switch, ordecreased navigation complexity in response to an unsuccessful selection of a prior target electronic control switch.

108. The apparatus of any of claims 101 through 107, wherein the result of the electronic testing activity comprises at least one of a response time, an accuracy, a reproducibility of the neural activity, or an error rate associated with a selection of one or more target electronic control switches.

109. The apparatus of any of claims 101 through 108, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:select, as the plurality of electronic control switches for display, a subset of electronic control switches having complexity levels not exceeding an ability level determined based at least in part on the electronic testing activity.

110. The apparatus of claim 109, wherein, to select the subset of electronic control switches, the processing system is configured to cause the apparatus to:select the subset of electronic control switches such that a complexity level of the display, computed based at least in part on a maximum, an average, or a weighted average of complexity levels of electronic control switches in the subset of electronic control switches, does not exceed the ability level.Attorney Docket No.: SYNC-N-Z054-00-WO111. The apparatus of any of claims 109 through 110, wherein:a complexity level of an electronic control switch is based at least in part on a traversal level and a selection level,the traversal level is based at least in part on an amount of time or a quantity of navigation steps for navigating to the electronic control switch, andthe selection level is based at least in part on a quantity of instances of the neural activity to select the electronic control switch.

112. The apparatus of any of claims 101 through 111, wherein, to provide the electronic testing activity, the processing system is configured to cause the apparatus to:initiate the electronic testing activity at least one of upon initial setup of the braincomputer interface, according to a schedule, in response to detected selection errors during non-testing use, or in response to a user selection of a testing command switch.

113. The apparatus of any of claims 101 through 112, wherein, to provide the electronic testing activity, the processing system is configured to cause the apparatus to:use a model to determine which target electronic control switches from a group of target electronic control switches to prompt the user to select.

114. The apparatus of claim 113, wherein the model uses an input of at least one of prior success or failure in selecting targets, an error rate, a response time, a traversal level, or a selection level, and outputs at least one of a next target electronic control switch or a next navigation complexity.

115. The apparatus of any of claims 101 through 114, wherein the electronic user interface is configured to adjust the complexity level of the display by increasing or decreasing a navigation complexity for the user to navigate the plurality of electronic control switches displayed by the electronic user interface.

116. The apparatus of any of claims 101 through 115, wherein the neural activity comprises an endogenous signal representative of neural activity detected by a neural interface device.

117. An apparatus, comprising:a processing system that includes processor circuitry and memory circuitry that stores code, the processing system configured to cause the apparatus to:provide a display on an electronic user interface operative with a braincomputer interface, wherein the display comprises a plurality of electronic control switches selectable using a neural activity of a user, and wherein the electronic user interface can adjust a complexity level of the display;monitor the user while engaging the electronic user interface to determine anAttorney Docket No.: SYNC-N-Z054-00-WOability level of the user to interact with the electronic user interface using the neural activity; andadjust the complexity level of the plurality of electronic control switches displayed by the electronic user interface based at least in part on the ability level of the user.

118. The apparatus of claim 117, wherein, to determine the ability level, the processing system is configured to cause the apparatus to:determine at least one of a response time for selection of an electronic control switch, an accuracy of selection of an electronic control switch, a reproducibility of neural activity used for selection, or an error rate for selection.

119. The apparatus of any of claims 117 through 118, wherein the ability level corresponds to a highest complexity level of an electronic control switch that the user is able to reliably select with less than a threshold error rate.

120. The apparatus of any of claims 117 through 119, wherein, to determine the ability level, the processing system is configured to cause the apparatus to:provide an electronic testing activity that prompts selection of one or more target electronic control switches having different navigation complexities; anddetermine the ability level based at least in part on a performance in the electronic testing activity.

121. The apparatus of claim 120, wherein, to determine the ability level, the processing system is configured to cause the apparatus to:determine a numerical level score based at least in part on a combination of (i) a quantity of navigation steps to reach each of the one or more target electronic control switches, and (ii) a quantity of selection inputs to select each of the one or more target electronic control switches.

122. The apparatus of any of claims 117 through 121, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:display a subset of the plurality of electronic control switches that excludes electronic control switches having complexity levels exceeding the ability level.

123. The apparatus of any of claims 117 through 122, wherein:the electronic user interface comprises a keyboard interface, andadjusting the complexity level comprises selecting a keyboard layout from a set of keyboard layouts comprising at least two of a QWERTY keyboard, an ABC keyboard, an ABC tiered keyboard, or a vowel-based keyboard.

124. The apparatus of any of claims 117 through 123, wherein, to adjust theAttorney Docket No.: SYNC-N-Z054-00-WOcomplexity level, the processing system is configured to cause the apparatus to:transition the electronic user interface among interface tiers that comprise at least a binary-choice interface tier and a keyboard interface tier.

125. The apparatus of claim 124, wherein transitioning among the interface tiers comprises displaying a binary-choice board comprising “yes” and “no” at a first tier of the interface tiers and displaying a full keyboard at a second tier of the interface tiers.

126. The apparatus of claim 125, wherein the processing system is further configured to cause the apparatus to:remove the binary-choice board from the display when the second tier is displayed.

127. The apparatus of any of claims 117 through 126, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:change an order or placement of an electronic control switch on the electronic user interface based at least in part on a frequency of selection of the electronic control switch.

128. The apparatus of any of claims 117 through 127, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:change at least one of a start position or a path of a navigation tool for the user to navigate among the plurality of electronic control switches based at least in part on a frequency of selection of one or more electronic control switches.

129. The apparatus of any of claims 117 through 128, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:change an algorithm used to process signals representative of the neural activity of the user to allow selection of an electronic control switch with more precise or less precise signals.

130. The apparatus of any of claims 117 through 129, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:change an algorithm that maps the neural activity to selection of the plurality of electronic control switches based at least in part on the ability level.

131. The apparatus of any of claims 117 through 130, wherein adjusting the complexity level is performed automatically without caregiver intervention, and the processing system is further configured to cause the apparatus to:limit an adjustment of the complexity level based at least in part on a maximum complexity level.

132. The apparatus of any of claims 117 through 131, wherein the ability level comprises a literacy score derived from at least one of a response time, an accuracy, a reproducibility of the neural activity, or an error rate associated with interaction with the electronic user interface across a plurality of sessions.Attorney Docket No.: SYNC-N-Z054-00-WO133. The apparatus of claim 132, wherein the literacy score comprises a braincomputer interface (BCI) literacy score.

134. The apparatus of any of claims 117 through 133, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:unlock one or more interface capabilities of the electronic user interface in response to the ability level meeting or exceeding a literacy score threshold.

135. The apparatus of any of claims 117 through 134, wherein, to monitor the user, the processing system is configured to cause the apparatus to:monitor the user while the user performs one or more activities of daily living using the electronic user interface, wherein the ability level is derived at least in part from a performance of the user during the one or more activities of daily living.

136. The apparatus of any of claims 117 through 135, wherein the electronic user interface comprises a game interface, and wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:modify a structure of the game interface based at least in part on the ability level of the user.

137. The apparatus of claim 136, wherein, to modify the structure of the game interface, the processing system is configured to cause the apparatus to:replace a full-input game control interface with a tiered input interface comprising a reduced set of electronic control switches corresponding to game actions available at the ability level of the user.

138. The apparatus of any of claims 117 through 137, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:generate one or more predictive control suggestions for display on the electronic user interface based at least in part on the ability level of the user and a predicted next interaction of the user with the electronic user interface.

139. The apparatus of any of claims 117 through 138, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:generate a set of electronic control switches for display on the electronic user interface using a language model, wherein the set of electronic control switches is generated based at least in part on a current application or screen associated with the electronic user interface.

140. An apparatus, comprising:a processing system that includes processor circuitry and memory circuitry that stores code, the processing system configured to cause the apparatus to:provide an electronic user interface for interacting with an electronic deviceAttorney Docket No.: SYNC-N-Z054-00-WOusing a plurality of electronic control switches displayed by the electronic user interface, wherein the electronic user interface can adjust a complexity level of a display of one or more of the plurality of electronic control switches;monitor a parameter associated with a user when the user engages the electronic user interface; andadjust the complexity level of the plurality of electronic control switches displayed based at least in part on the parameter associated with the user.

141. The apparatus of claim 140, wherein the parameter associated with the user comprises a physiological parameter selected from a heart rate, a body temperature, a blood pressure, a breathing rate, or a pupil dilation.

142. The apparatus of any of claims 140 through 141, wherein:the parameter associated with the user comprises a location of the user, and adjusting the complexity level comprises presenting control switches associated with a location-specific task.

143. The apparatus of any of claims 140 through 142, wherein:the parameter associated with the user comprises a time of day, andadjusting the complexity level comprises decreasing the complexity level at nighttime.

144. The apparatus of any of claims 140 through 143, wherein the parameter associated with the user comprises at least one of an error rate or a response time associated with selection of the plurality of electronic control switches during non-testing use.

145. The apparatus of any of claims 140 through 144, wherein:the parameter associated with the user comprises a use history indicating a frequency of selection of one or more electronic control switches, andadjusting the complexity level comprises relocating at least one of the one or more electronic control switches.

146. The apparatus of any of claims 140 through 145, wherein the parameter associated with the user comprises an ability level of the user to interact with the electronic user interface.

147. The apparatus of any of claims 140 through 146, wherein monitoring the parameter associated with the user comprises receiving the parameter from at least one of an external device, a personal electronic device, or a remote server.

148. The apparatus of any of claims 140 through 147, wherein adjusting the complexity level is based at least in part on aggregating a plurality of parameters associated with the user to determine the complexity level.

149. The apparatus of any of claims 140 through 148, wherein:Attorney Docket No.: SYNC-N-Z054-00-WOthe electronic user interface can operate with a brain-computer interface, and each of the plurality of electronic control switches is selectable using a neural activity of the user.

150. The apparatus of any of claims 140 through 149, wherein the parameter associated with the user comprises a brain-computer interface literacy score derived from at least one of a response time, an accuracy, a reproducibility of a neural activity, or an error rate associated with interaction with the electronic user interface across a plurality of sessions.

151. The apparatus of any of claims 140 through 150, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:unlock one or more interface capabilities of the electronic user interface in response to the parameter meeting or exceeding a literacy threshold.

152. The apparatus of any of claims 140 through 151, wherein, to monitor the parameter associated with the user, the processing system is configured to cause the apparatus to:monitor the user while performing one or more activities of daily living using the electronic user interface, wherein the parameter is derived at least in part from a performance of the user during the one or more activities of daily living.

153. The apparatus of any of claims 140 through 152, wherein the electronic user interface comprises a game interface, and wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:modify a structure of the game interface based at least in part on the parameter associated with the user.

154. The apparatus of claim 153, wherein, to modify the structure of the game interface, the processing system is configured to cause the apparatus to:replace a full-input game control interface with a tiered input interface comprising a reduced set of electronic control switches corresponding to game actions available based on the parameter associated with the user.

155. The apparatus of any of claims 140 through 154, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:generate one or more predictive control suggestions for display on the electronic user interface based at least in part on the parameter associated with the user and a predicted next interaction of the user with the electronic user interface.

156. The apparatus of any of claims 140 through 155, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:generate a set of electronic control switches for display on the electronic user interfaceAttorney Docket No.: SYNC-N-Z054-00-WOusing a language model, wherein the set of electronic control switches is generated based at least in part on a current application or screen associated with the electronic user interface.

157. An apparatus, comprising:a processing system that includes processor circuitry and memory circuitry that stores code, the processing system configured to cause the apparatus to:provide an electronic user interface that comprises a plurality of electronic control switches and a navigation tool for guiding navigation among the plurality of electronic control switches;determine a traversal level for at least one electronic control switch based at least in part on an amount of time for a user to navigate to the at least one electronic control switch using the navigation tool;determine a selection level for the at least one electronic control switch based at least in part on a quantity of instances of a selection input by the user to select the at least one electronic control switch; andadjust the electronic user interface to be associated with a complexity level that is based at least in part on the traversal level and the selection level.

158. The apparatus of claim 157, wherein the processing system is further configured to cause the apparatus to:determine the complexity level for the electronic user interface based at least in part on a combination of the traversal level and the selection level.

159. The apparatus of any of claims 157 through 158, wherein the processing system is further configured to cause the apparatus to:determine the complexity level based at least in part on a maximum complexity level among the plurality of electronic control switches displayed or based at least in part on an average or weighted average of complexity levels of a subset of the plurality of electronic control switches displayed.

160. The apparatus of any of claims 157 through 159, wherein the navigation tool comprises an indicator, an effector, or a cursor that is displayed on the electronic user interface and that guides navigation among the plurality of electronic control switches.

161. The apparatus of any of claims 157 through 160, wherein, to determine the traversal level, the processing system is configured to cause the apparatus to:determine a quantity of navigation steps or scan cycles to navigate to the at least one electronic control switch using the navigation tool.

162. The apparatus of any of claims 157 through 161, wherein the selection input comprises neural activity of the user.Attorney Docket No.: SYNC-N-Z054-00-WO163. The apparatus of any of claims 157 through 162, wherein, to determine the selection level, the processing system is configured to cause the apparatus to:apply a weight to a selection input type of the selection input based at least in part on a difficulty of engaging in the selection input type.

164. The apparatus of claim 163, wherein the weight is user specific.

165. The apparatus of any of claims 157 through 164, wherein, to adjust the electronic user interface, the processing system is configured to cause the apparatus to:select a subset of electronic control switches for display based at least in part on a rank or level assigned to each electronic control switch, wherein the rank or level is set by at least one of the user, a caregiver, or the electronic user interface.

166. The apparatus of any of claims 157 through 165, wherein the processing system is further configured to cause the apparatus to:determine the traversal level and the selection level during an electronic testing activity that prompts selection of one or more target electronic control switches.

167. The apparatus of claim 166, wherein the electronic testing activity comprises a single-switch scanner test or a multi-action scanner test that uses different forms of neural activity to access different rows, columns, or subsets of electronic control switches.

168. The apparatus of any of claims 157 through 167, wherein, to adjust the electronic user interface, the processing system is configured to cause the apparatus to:transition among interface tiers comprising a binary-choice interface tier and a keyboard interface tier, comprising selecting a keyboard layout from a set of keyboard layouts comprising at least two of a QWERTY keyboard, an ABC keyboard, an ABC tiered keyboard, or a vowel-based keyboard.

169. An apparatus, comprising:a processing system that includes processor circuitry and memory circuitry that stores code, the processing system configured to cause the apparatus to:provide an electronic user interface that comprises a plurality of electronic control switches selectable by a user, wherein the electronic user interface can adjust a complexity level of a display of the plurality of electronic control switches;monitor the user while the user engages with the electronic user interface to determine an actual interaction rate for the user; andadjust the complexity level based at least in part on a comparison of the actual interaction rate to an expected interaction rate associated with a current complexity level for the user.

170. The apparatus of claim 169, wherein monitoring to determine the actualAttorney Docket No.: SYNC-N-Z054-00-WOinteraction rate comprises computing the actual interaction rate over a rolling window of one or more interaction cycles.

171. The apparatus of any of claims 169 through 170, wherein the electronic user interface comprises a scanning interface that sweeps through a quantity of electronic control switches before repeating.

172. The apparatus of any of claims 169 through 171, wherein adjusting the complexity level comprises at least one of increasing or decreasing a quantity of electronic control switches displayed or switching among interface tiers.

173. The apparatus of any of claims 169 through 172, wherein, to adjust the complexity level, the processing system is configured to cause the apparatus to:change a hierarchical depth of the electronic user interface or changing a quantity of menus navigated by the user to reach a target electronic control switch.

174. The apparatus of any of claims 169 through 173, wherein the plurality of electronic control switches are selectable using a neural activity of the user.

175. The apparatus of any of claims 169 through 174, wherein, to determine the expected interaction rate, the processing system is configured to cause the apparatus to:determine a baseline interaction rate during an initial portion of a session or retrieving the baseline interaction rate from a prior session.

176. The apparatus of any of claims 169 through 175, wherein, to determine the expected interaction rate, the processing system is configured to cause the apparatus to:update the expected interaction rate using an exponential moving average based at least in part on one or more prior actual interaction rates.

177. The apparatus of any of claims 169 through 176, wherein:the comparison yields a pacing index, andadjusting the complexity level comprises increasing the complexity level when the pacing index exceeds a first threshold or decreasing the complexity level when the pacing index is below a second threshold.

178. The apparatus of claim 177, wherein:increasing the complexity level comprises adding additional electronic control switches to the display or increasing a density of electronic control switches, anddecreasing the complexity level comprises removing electronic control switches from the display or decreasing the density of electronic control switches.

179. The apparatus of any of claims 169 through 178, wherein the processing system is further configured to cause the apparatus to:provide a notification to the user that a modified user interface is available prior toAttorney Docket No.: SYNC-N-Z054-00-WOadjusting the complexity level.

180. The apparatus of any of claims 169 through 179, wherein the processing system is further configured to cause the apparatus to:receive a user confirmation prior to adjusting the complexity level.

181. The apparatus of any of claims 169 through 180, wherein the processing system is further configured to cause the apparatus to:provide, in response to determining that the actual interaction rate falls below the expected interaction rate by more than a threshold amount, at least one of predictive text or communication assistance on the electronic user interface to reduce a selection burden on the user.

182. The apparatus of claim 181, wherein, to provide the predictive text or the communication assistance, the processing system is configured to cause the apparatus to: display one or more predicted word or phrase completions on the electronic user interface based at least in part on a prior interaction history of the user.

183. An apparatus, comprising:a processing system that includes processor circuitry and memory circuitry that stores code, the processing system configured to cause the apparatus to:provide a display on an electronic user interface that comprises a base arrangement of electronic control switches and comprises a control setting configured to enable an additive display mode, wherein the electronic user interface can selectively add an additional region or pane comprising alternative electronic control switches without changing the base arrangement when the additive display mode is enabled; monitor user interaction with the base arrangement while the additive display mode is enabled;determine that the base arrangement exceeds a capability of a user based at least in part on the user interaction with the base arrangement; andadd, to the display and in response to determining that the base arrangement exceeds the capability of the user, the additional region or pane comprising the alternative electronic control switches without changing the base arrangement.

184. The apparatus of claim 183, wherein the alternative electronic control switches are simplified electronic control switches relative to the electronic control switches of the base arrangement.

185. The apparatus of any of claims 183 through 184, wherein:the additive display mode is an agentic mode, andenabling the additive display mode disables a leveling mode that changes the baseAttorney Docket No.: SYNC-N-Z054-00-WOarrangement.

186. The apparatus of any of claims 183 through 185, wherein the additional region or pane comprises an additional row of electronic control switches.

187. The apparatus of any of claims 183 through 186, wherein, to determine that the base arrangement exceeds the capability of the user, the processing system is configured to cause the apparatus to:determine that the user fails to select a desired electronic control switch within a time threshold or that an error rate associated with selection exceeds an error threshold.

188. The apparatus of any of claims 183 through 187, wherein the capability of the user comprises an ability level determined based at least in part on an electronic testing activity.

189. The apparatus of any of claims 183 through 188, wherein the alternative electronic control switches correspond to at least one of a simplified keyboard interface or a binary-choice interface.

190. The apparatus of any of claims 183 through 189, wherein the alternative electronic control switches correspond to at least one of a simplified game interface or a media control interface.

191. The apparatus of any of claims 183 through 190, wherein:the alternative electronic control switches comprise context-based suggestions determined based at least in part on a current screen or application of the electronic user interface, andthe context-based suggestions are generated using a language model.

192. The apparatus of any of claims 183 through 191, wherein the processing system is further configured to cause the apparatus to:store a user preference for the additive display mode; andapply the user preference in a subsequent session, wherein the electronic user interface can receive a user input to dismiss the additional region or pane after it is added.

193. The apparatus of any of claims 183 through 192, wherein, to determine that the base arrangement exceeds the capability of the user, the processing system is configured to cause the apparatus to:operate the electronic user interface as a scanning interface that sequentially highlights a plurality of the electronic control switches in interaction cycles;computing, over a rolling window of interaction cycles, a selection strike rate as a ratio of (i) a sum of scoring weights for interaction cycles in which a selection occur to (ii) a sum of opportunity weights for interaction cycles in the rolling window, wherein opportunity weightsAttorney Docket No.: SYNC-N-Z054-00-WOof the sum of opportunity weights are based at least in part on a rest factor assigned to nonselected electronic control switches and scoring weights of the sum of scoring weights are based at least in part on a bonus factor that increases credit for selections made in longer interaction cycles;compute a pacing index based at least in part on a ratio of the selection strike rate relative to a baseline selection strike rate for the user; anddetermine that the base arrangement exceeds the capability of the user when the pacing index is below a threshold.

194. An apparatus, comprising:a processing system that includes processor circuitry and memory circuitry that stores code, the processing system configured to cause the apparatus to:provide a display on an electronic user interface operative with a braincomputer interface, wherein the display comprises a plurality of electronic control switches selectable using a neural activity of a user, and wherein the electronic user interface can adjust a complexity level of the display among a plurality of interface tiers including a highest interface tier;determine whether the user is able to interact with the electronic user interface at the highest interface tier across a threshold quantity of sessions; andgenerate a graduation indicator in response to determining that the user is able to interact with the electronic user interface at the highest interface tier across the threshold quantity of sessions, wherein the graduation indicator indicates a recommendation for the user to transition to a non-adapting user interface that operates without complexity adjustment based on an ability level of the user.

195. The apparatus of claim 194, wherein the threshold quantity of sessions comprises a predetermined quantity of consecutive sessions in which the user has consistently interacted with the electronic user interface at the highest interface tier.

196. The apparatus of any of claims 194 through 195, wherein, to determine whether the user has interacted with the electronic user interface at the highest interface tier, the processing system is configured to cause the apparatus to:determine that at least one of a response time, an accuracy, a reproducibility of the neural activity, or an error rate associated with interaction at the highest interface tier meets or exceeds a performance threshold across the threshold quantity of sessions.

197. The apparatus of any of claims 194 through 196, wherein the processing system is further configured to cause the apparatus to:transmit the graduation indicator to at least one of a caregiver or a clinician associatedAttorney Docket No.: SYNC-N-Z054-00-WOwith the user.

198. The apparatus of any of claims 194 through 197, wherein:the plurality of interface tiers comprises at least a binary-choice interface tier, a keyboard interface tier, and the highest interface tier, andthe highest interface tier corresponds to a full-complexity interface.

199. The apparatus of any of claims 194 through 198, wherein the processing system is further configured to cause the apparatus to:generate a consistency score based on an interaction of the user with the electronic user interface at the highest interface tier across a plurality of sessions, wherein generating the graduation indicator is triggered when the consistency score exceeds a graduation threshold.

200. The apparatus of any of claims 194 through 199, wherein the graduation indicator comprises at least one of a visual notification displayed on the electronic user interface or an auditory notification.

201. A non-transitory computer-readable medium storing code, the code comprising instructions executable by one or more processors to:provide a display on an electronic user interface operative with a brain-computer interface, wherein the display comprises a plurality of electronic control switches selectable using a neural activity of a user, and wherein the electronic user interface can adjust a complexity level of the display;provide an electronic testing activity for the neural activity on the electronic user interface; andadjust the complexity level of the display based at least in part on a result of the electronic testing activity.

202. The non-transitory computer-readable medium of claim 201, wherein the instructions are further executable by the one or more processors to:monitor the electronic testing activity during engagement by the user, wherein adjusting the complexity level is in accordance with monitoring the electronic testing activity during the engagement by the user.

203. The non-transitory computer-readable medium of any of claims 201 through 202, wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:increase or decrease a quantity of the plurality of electronic control switches displayed on the electronic user interface.

204. The non-transitory computer-readable medium of any of claims 201 through 203, wherein, to adjust the complexity level, the instructions are executable by the one or moreAttorney Docket No.: SYNC-N-Z054-00-WOprocessors to:change at least one of a layout, a spacing, a density, a size, a color, a contrast, a text label, an order, or a placement of one or more of the plurality of electronic control switches.

205. The non-transitory computer-readable medium of any of claims 201 through 204, wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:change at least one of a speed or a path of a navigation tool for the user to navigate among the plurality of electronic control switches.

206. The non-transitory computer-readable medium of any of claims 201 through 205, wherein, to provide the electronic testing activity, the instructions are executable by the one or more processors to:prompt the user to select a target electronic control switch displayed on the electronic user interface.

207. The non-transitory computer-readable medium of claim 206, wherein, to prompt the user to select the target electronic control switch, the instructions are executable by the one or more processors to:iteratively prompt the user to select additional target electronic control switches having: increased navigation complexity in response to a successful selection of a prior target electronic control switch, ordecreased navigation complexity in response to an unsuccessful selection of a prior target electronic control switch.

208. The non-transitory computer-readable medium of any of claims 201 through 207, wherein the result of the electronic testing activity comprises at least one of a response time, an accuracy, a reproducibility of the neural activity, or an error rate associated with a selection of one or more target electronic control switches.

209. The non-transitory computer-readable medium of any of claims 201 through 208, wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:select, as the plurality of electronic control switches for display, a subset of electronic control switches having complexity levels not exceeding an ability level determined based at least in part on the electronic testing activity.

210. The non-transitory computer-readable medium of claim 209, wherein, to select the subset of electronic control switches, the instructions are executable by the one or more processors to:select the subset of electronic control switches such that a complexity level of theAttorney Docket No.: SYNC-N-Z054-00-WOdisplay, computed based at least in part on a maximum, an average, or a weighted average of complexity levels of electronic control switches in the subset of electronic control switches, does not exceed the ability level.

211. The non-transitory computer-readable medium of any of claims 209 through 210, wherein:a complexity level of an electronic control switch is based at least in part on a traversal level and a selection level,the traversal level is based at least in part on an amount of time or a quantity of navigation steps for navigating to the electronic control switch, andthe selection level is based at least in part on a quantity of instances of the neural activity to select the electronic control switch.

212. The non-transitory computer-readable medium of any of claims 201 through 211, wherein, to provide the electronic testing activity, the instructions are executable by the one or more processors to:initiate the electronic testing activity at least one of upon initial setup of the braincomputer interface, according to a schedule, in response to detected selection errors during non-testing use, or in response to a user selection of a testing command switch.

213. The non-transitory computer-readable medium of any of claims 201 through 212, wherein, to provide the electronic testing activity, the instructions are executable by the one or more processors to:use a model to determine which target electronic control switches from a group of target electronic control switches to prompt the user to select.

214. The non-transitory computer-readable medium of claim 213, wherein the model uses an input of at least one of prior success or failure in selecting targets, an error rate, a response time, a traversal level, or a selection level, and outputs at least one of a next target electronic control switch or a next navigation complexity.

215. The non-transitory computer-readable medium of any of claims 201 through 214, wherein the electronic user interface is configured to adjust the complexity level of the display by increasing or decreasing a navigation complexity for the user to navigate the plurality of electronic control switches displayed by the electronic user interface.

216. The non-transitory computer-readable medium of any of claims 201 through 215, wherein the neural activity comprises an endogenous signal representative of neural activity detected by a neural interface device.

217. A non-transitory computer-readable medium storing code, the code comprising instructions executable by one or more processors to:Attorney Docket No.: SYNC-N-Z054-00-WOprovide a display on an electronic user interface operative with a brain-computer interface, wherein the display comprises a plurality of electronic control switches selectable using a neural activity of a user, and wherein the electronic user interface can adjust a complexity level of the display;monitor the user while engaging the electronic user interface to determine an ability level of the user to interact with the electronic user interface using the neural activity; and adjust the complexity level of the plurality of electronic control switches displayed by the electronic user interface based at least in part on the ability level of the user.

218. The non-transitory computer-readable medium of claim 217, wherein, to determine the ability level, the instructions are executable by the one or more processors to: determine at least one of a response time for selection of an electronic control switch, an accuracy of selection of an electronic control switch, a reproducibility of neural activity used for selection, or an error rate for selection.

219. The non-transitory computer-readable medium of any of claims 217 through 218, wherein the ability level corresponds to a highest complexity level of an electronic control switch that the user is able to reliably select with less than a threshold error rate.

220. The non-transitory computer-readable medium of any of claims 217 through 219, wherein, to determine the ability level, the instructions are executable by the one or more processors to:provide an electronic testing activity that prompts selection of one or more target electronic control switches having different navigation complexities; anddetermine the ability level based at least in part on a performance in the electronic testing activity.

221. The non-transitory computer-readable medium of claim 220, wherein, to determine the ability level, the instructions are executable by the one or more processors to: determine a numerical level score based at least in part on a combination of (i) a quantity of navigation steps to reach each of the one or more target electronic control switches, and (ii) a quantity of selection inputs to select each of the one or more target electronic control switches.

222. The non-transitory computer-readable medium of any of claims 217 through 221, wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:display a subset of the plurality of electronic control switches that excludes electronic control switches having complexity levels exceeding the ability level.

223. The non-transitory computer-readable medium of any of claims 217 throughAttorney Docket No.: SYNC-N-Z054-00-WO222, wherein:the electronic user interface comprises a keyboard interface, andadjusting the complexity level comprises selecting a keyboard layout from a set of keyboard layouts comprising at least two of a QWERTY keyboard, an ABC keyboard, an ABC tiered keyboard, or a vowel-based keyboard.

224. The non-transitory computer-readable medium of any of claims 217 through 223, wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:transition the electronic user interface among interface tiers that comprise at least a binary-choice interface tier and a keyboard interface tier.

225. The non-transitory computer-readable medium of claim 224, wherein transitioning among the interface tiers comprises displaying a binary-choice board comprising “yes” and “no” at a first tier of the interface tiers and displaying a full keyboard at a second tier of the interface tiers.

226. The non-transitory computer-readable medium of claim 225, wherein the instructions are further executable by the one or more processors to:remove the binary-choice board from the display when the second tier is displayed.

227. The non-transitory computer-readable medium of any of claims 217 through 226, wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:change an order or placement of an electronic control switch on the electronic user interface based at least in part on a frequency of selection of the electronic control switch.

228. The non-transitory computer-readable medium of any of claims 217 through 227, wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:change at least one of a start position or a path of a navigation tool for the user to navigate among the plurality of electronic control switches based at least in part on a frequency of selection of one or more electronic control switches.

229. The non-transitory computer-readable medium of any of claims 217 through 228, wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:change an algorithm used to process signals representative of the neural activity of the user to allow selection of an electronic control switch with more precise or less precise signals.

230. The non-transitory computer-readable medium of any of claims 217 through 229, wherein, to adjust the complexity level, the instructions are executable by the one or moreAttorney Docket No.: SYNC-N-Z054-00-WOprocessors to:change an algorithm that maps the neural activity to selection of the plurality of electronic control switches based at least in part on the ability level.

231. The non-transitory computer-readable medium of any of claims 217 through 230, wherein adjusting the complexity level is performed automatically without caregiver intervention, and the instructions are further executable by the one or more processors to: limit an adjustment of the complexity level based at least in part on a maximum complexity level.

232. The non-transitory computer-readable medium of any of claims 217 through 231, wherein the ability level comprises a literacy score derived from at least one of a response time, an accuracy, a reproducibility of the neural activity, or an error rate associated with interaction with the electronic user interface across a plurality of sessions.

233. The non-transitory computer-readable medium of claim 232, wherein the literacy score comprises a brain-computer interface (BCI) literacy score.

234. The non-transitory computer-readable medium of any of claims 217 through 233, wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:unlock one or more interface capabilities of the electronic user interface in response to the ability level meeting or exceeding a literacy score threshold.

235. The non-transitory computer-readable medium of any of claims 217 through 234, wherein, to monitor the user, the instructions are executable by the one or more processors to:monitor the user while the user performs one or more activities of daily living using the electronic user interface, wherein the ability level is derived at least in part from a performance of the user during the one or more activities of daily living.

236. The non-transitory computer-readable medium of any of claims 217 through 235, wherein the electronic user interface comprises a game interface, and wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:modify a structure of the game interface based at least in part on the ability level of the user.

237. The non-transitory computer-readable medium of claim 236, wherein, to modify the structure of the game interface, the instructions are executable by the one or more processors to:replace a full-input game control interface with a tiered input interface comprising a reduced set of electronic control switches corresponding to game actions available at the abilityAttorney Docket No.: SYNC-N-Z054-00-WOlevel of the user.

238. The non-transitory computer-readable medium of any of claims 217 through 237, wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:generate one or more predictive control suggestions for display on the electronic user interface based at least in part on the ability level of the user and a predicted next interaction of the user with the electronic user interface.

239. The non-transitory computer-readable medium of any of claims 217 through 238, wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:generate a set of electronic control switches for display on the electronic user interface using a language model, wherein the set of electronic control switches is generated based at least in part on a current application or screen associated with the electronic user interface.

240. A non-transitory computer-readable medium storing code, the code comprising instructions executable by one or more processors to:provide an electronic user interface for interacting with an electronic device using a plurality of electronic control switches displayed by the electronic user interface, wherein the electronic user interface can adjust a complexity level of a display of one or more of the plurality of electronic control switches;monitor a parameter associated with a user when the user engages the electronic user interface; andadjust the complexity level of the plurality of electronic control switches displayed based at least in part on the parameter associated with the user.

241. The non-transitory computer-readable medium of claim 240, wherein the parameter associated with the user comprises a physiological parameter selected from a heart rate, a body temperature, a blood pressure, a breathing rate, or a pupil dilation.

242. The non-transitory computer-readable medium of any of claims 240 through 241, wherein:the parameter associated with the user comprises a location of the user, and adjusting the complexity level comprises presenting control switches associated with a location-specific task.

243. The non-transitory computer-readable medium of any of claims 240 through 242, wherein:the parameter associated with the user comprises a time of day, andadjusting the complexity level comprises decreasing the complexity level at nighttime.Attorney Docket No.: SYNC-N-Z054-00-WO244. The non-transitory computer-readable medium of any of claims 240 through 243, wherein the parameter associated with the user comprises at least one of an error rate or a response time associated with selection of the plurality of electronic control switches during non-testing use.

245. The non-transitory computer-readable medium of any of claims 240 through 244, wherein:the parameter associated with the user comprises a use history indicating a frequency of selection of one or more electronic control switches, andadjusting the complexity level comprises relocating at least one of the one or more electronic control switches.

246. The non-transitory computer-readable medium of any of claims 240 through 245, wherein the parameter associated with the user comprises an ability level of the user to interact with the electronic user interface.

247. The non-transitory computer-readable medium of any of claims 240 through 246, wherein monitoring the parameter associated with the user comprises receiving the parameter from at least one of an external device, a personal electronic device, or a remote server.

248. The non-transitory computer-readable medium of any of claims 240 through 247, wherein adjusting the complexity level is based at least in part on aggregating a plurality of parameters associated with the user to determine the complexity level.

249. The non-transitory computer-readable medium of any of claims 240 through 248, wherein:the electronic user interface can operate with a brain-computer interface, and each of the plurality of electronic control switches is selectable using a neural activity of the user.

250. The non-transitory computer-readable medium of any of claims 240 through 249, wherein the parameter associated with the user comprises a brain-computer interface literacy score derived from at least one of a response time, an accuracy, a reproducibility of a neural activity, or an error rate associated with interaction with the electronic user interface across a plurality of sessions.

251. The non-transitory computer-readable medium of any of claims 240 through 250, wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:unlock one or more interface capabilities of the electronic user interface in response to the parameter meeting or exceeding a literacy threshold.Attorney Docket No.: SYNC-N-Z054-00-WO252. The non-transitory computer-readable medium of any of claims 240 through 251, wherein, to monitor the parameter associated with the user, the instructions are executable by the one or more processors to:monitor the user while performing one or more activities of daily living using the electronic user interface, wherein the parameter is derived at least in part from a performance of the user during the one or more activities of daily living.

253. The non-transitory computer-readable medium of any of claims 240 through 252, wherein the electronic user interface comprises a game interface, and wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:modify a structure of the game interface based at least in part on the parameter associated with the user.

254. The non-transitory computer-readable medium of claim 253, wherein, to modify the structure of the game interface, the instructions are executable by the one or more processors to:replace a full-input game control interface with a tiered input interface comprising a reduced set of electronic control switches corresponding to game actions available based on the parameter associated with the user.

255. The non-transitory computer-readable medium of any of claims 240 through 254, wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:generate one or more predictive control suggestions for display on the electronic user interface based at least in part on the parameter associated with the user and a predicted next interaction of the user with the electronic user interface.

256. The non-transitory computer-readable medium of any of claims 240 through 255, wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:generate a set of electronic control switches for display on the electronic user interface using a language model, wherein the set of electronic control switches is generated based at least in part on a current application or screen associated with the electronic user interface.

257. A non-transitory computer-readable medium storing code, the code comprising instructions executable by one or more processors to:provide an electronic user interface that comprises a plurality of electronic control switches and a navigation tool for guiding navigation among the plurality of electronic control switches;determine a traversal level for at least one electronic control switch based at least inAttorney Docket No.: SYNC-N-Z054-00-WOpart on an amount of time for a user to navigate to the at least one electronic control switch using the navigation tool;determine a selection level for the at least one electronic control switch based at least in part on a quantity of instances of a selection input by the user to select the at least one electronic control switch; andadjust the electronic user interface to be associated with a complexity level that is based at least in part on the traversal level and the selection level.

258. The non-transitory computer-readable medium of claim 257, wherein the instructions are further executable by the one or more processors to:determine the complexity level for the electronic user interface based at least in part on a combination of the traversal level and the selection level.

259. The non-transitory computer-readable medium of any of claims 257 through 258, wherein the instructions are further executable by the one or more processors to:determine the complexity level based at least in part on a maximum complexity level among the plurality of electronic control switches displayed or based at least in part on an average or weighted average of complexity levels of a subset of the plurality of electronic control switches displayed.

260. The non-transitory computer-readable medium of any of claims 257 through 259, wherein the navigation tool comprises an indicator, an effector, or a cursor that is displayed on the electronic user interface and that guides navigation among the plurality of electronic control switches.

261. The non-transitory computer-readable medium of any of claims 257 through 260, wherein, to determine the traversal level, the instructions are executable by the one or more processors to:determine a quantity of navigation steps or scan cycles to navigate to the at least one electronic control switch using the navigation tool.

262. The non-transitory computer-readable medium of any of claims 257 through 261, wherein the selection input comprises neural activity of the user.

263. The non-transitory computer-readable medium of any of claims 257 through 262, wherein, to determine the selection level, the instructions are executable by the one or more processors to:apply a weight to a selection input type of the selection input based at least in part on a difficulty of engaging in the selection input type.

264. The non-transitory computer-readable medium of claim 263, wherein the weight is user specific.Attorney Docket No.: SYNC-N-Z054-00-WO265. The non-transitory computer-readable medium of any of claims 257 through 264, wherein, to adjust the electronic user interface, the instructions are executable by the one or more processors to:select a subset of electronic control switches for display based at least in part on a rank or level assigned to each electronic control switch, wherein the rank or level is set by at least one of the user, a caregiver, or the electronic user interface.

266. The non-transitory computer-readable medium of any of claims 257 through 265, wherein the instructions are further executable by the one or more processors to:determine the traversal level and the selection level during an electronic testing activity that prompts selection of one or more target electronic control switches.

267. The non-transitory computer-readable medium of claim 266, wherein the electronic testing activity comprises a single-switch scanner test or a multi-action scanner test that uses different forms of neural activity to access different rows, columns, or subsets of electronic control switches.

268. The non-transitory computer-readable medium of any of claims 257 through 267, wherein, to adjust the electronic user interface, the instructions are executable by the one or more processors to:transition among interface tiers comprising a binary-choice interface tier and a keyboard interface tier, comprising selecting a keyboard layout from a set of keyboard layouts comprising at least two of a QWERTY keyboard, an ABC keyboard, an ABC tiered keyboard, or a vowel-based keyboard.

269. A non-transitory computer-readable medium storing code, the code comprising instructions executable by one or more processors to:provide an electronic user interface that comprises a plurality of electronic control switches selectable by a user, wherein the electronic user interface can adjust a complexity level of a display of the plurality of electronic control switches;monitor the user while the user engages with the electronic user interface to determine an actual interaction rate for the user; andadjust the complexity level based at least in part on a comparison of the actual interaction rate to an expected interaction rate associated with a current complexity level for the user.

270. The non-transitory computer-readable medium of claim 269, wherein monitoring to determine the actual interaction rate comprises computing the actual interaction rate over a rolling window of one or more interaction cycles.

271. The non-transitory computer-readable medium of any of claims 269 throughAttorney Docket No.: SYNC-N-Z054-00-WO270, wherein the electronic user interface comprises a scanning interface that sweeps through a quantity of electronic control switches before repeating.

272. The non-transitory computer-readable medium of any of claims 269 through 271, wherein adjusting the complexity level comprises at least one of increasing or decreasing a quantity of electronic control switches displayed or switching among interface tiers.

273. The non-transitory computer-readable medium of any of claims 269 through 272, wherein, to adjust the complexity level, the instructions are executable by the one or more processors to:change a hierarchical depth of the electronic user interface or change a quantity of menus navigated by the user to reach a target electronic control switch.

274. The non-transitory computer-readable medium of any of claims 269 through 273, wherein the plurality of electronic control switches are selectable using a neural activity of the user.

275. The non-transitory computer-readable medium of any of claims 269 through 274, wherein, to determine the expected interaction rate, the instructions are executable by the one or more processors to:determine a baseline interaction rate during an initial portion of a session or retrieve the baseline interaction rate from a prior session.

276. The non-transitory computer-readable medium of any of claims 269 through 275, wherein, to determine the expected interaction rate, the instructions are executable by the one or more processors to:update the expected interaction rate using an exponential moving average based at least in part on one or more prior actual interaction rates.

277. The non-transitory computer-readable medium of any of claims 269 through 276, wherein:the comparison yields a pacing index, andadjusting the complexity level comprises increasing the complexity level when the pacing index exceeds a first threshold or decreasing the complexity level when the pacing index is below a second threshold.

278. The non-transitory computer-readable medium of claim 277, wherein: increasing the complexity level comprises adding additional electronic control switches to the display or increasing a density of electronic control switches, anddecreasing the complexity level comprises removing electronic control switches from the display or decreasing the density of electronic control switches.

279. The non-transitory computer-readable medium of any of claims 269 throughAttorney Docket No.: SYNC-N-Z054-00-WO278, wherein the instructions are further executable by the one or more processors to:provide a notification to the user that a modified user interface is available prior to adjusting the complexity level.

280. The non-transitory computer-readable medium of any of claims 269 through 279, wherein the instructions are further executable by the one or more processors to:receive a user confirmation prior to adjusting the complexity level.

281. The non-transitory computer-readable medium of any of claims 269 through 280, wherein the instructions are further executable by the one or more processors to:provide, in response to determining that the actual interaction rate falls below the expected interaction rate by more than a threshold amount, at least one of predictive text or communication assistance on the electronic user interface to reduce a selection burden on the user.

282. The non-transitory computer-readable medium of claim 281, wherein, to provide the predictive text or the communication assistance, the instructions are executable by the one or more processors to:display one or more predicted word or phrase completions on the electronic user interface based at least in part on a prior interaction history of the user.

283. A non-transitory computer-readable medium storing code, the code comprising instructions executable by one or more processors to:provide a display on an electronic user interface that comprises a base arrangement of electronic control switches and comprises a control setting configured to enable an additive display mode, wherein the electronic user interface can selectively add an additional region or pane comprising alternative electronic control switches without changing the base arrangement when the additive display mode is enabled;monitor user interaction with the base arrangement while the additive display mode is enabled;determine that the base arrangement exceeds a capability of a user based at least in part on the user interaction with the base arrangement; andadd, to the display and in response to determining that the base arrangement exceeds the capability of the user, the additional region or pane comprising the alternative electronic control switches without changing the base arrangement.

284. The non-transitory computer-readable medium of claim 283, wherein the alternative electronic control switches are simplified electronic control switches relative to the electronic control switches of the base arrangement.

285. The non-transitory computer-readable medium of any of claims 283 throughAttorney Docket No.: SYNC-N-Z054-00-WO284, wherein:the additive display mode is an agentic mode, andenabling the additive display mode disables a leveling mode that changes the base arrangement.

286. The non-transitory computer-readable medium of any of claims 283 through 285, wherein the additional region or pane comprises an additional row of electronic control switches.

287. The non-transitory computer-readable medium of any of claims 283 through 286, wherein, to determine that the base arrangement exceeds the capability of the user, the instructions are executable by the one or more processors to:determine that the user fails to select a desired electronic control switch within a time threshold or that an error rate associated with selection exceeds an error threshold.

288. The non-transitory computer-readable medium of any of claims 283 through 287, wherein the capability of the user comprises an ability level determined based at least in part on an electronic testing activity.

289. The non-transitory computer-readable medium of any of claims 283 through 288, wherein the alternative electronic control switches correspond to at least one of a simplified keyboard interface or a binary-choice interface.

290. The non-transitory computer-readable medium of any of claims 283 through 289, wherein the alternative electronic control switches correspond to at least one of a simplified game interface or a media control interface.

291. The non-transitory computer-readable medium of any of claims 283 through 290, wherein:the alternative electronic control switches comprise context-based suggestions determined based at least in part on a current screen or application of the electronic user interface, andthe context-based suggestions are generated using a language model.

292. The non-transitory computer-readable medium of any of claims 283 through 291, wherein the instructions are further executable by the one or more processors to:store a user preference for the additive display mode; andapply the user preference in a subsequent session, wherein the electronic user interface can receive a user input to dismiss the additional region or pane after it is added.

293. The non-transitory computer-readable medium of any of claims 283 through 292, wherein, to determine that the base arrangement exceeds the capability of the user, the instructions are executable by the one or more processors to:Attorney Docket No.: SYNC-N-Z054-00-WOoperate the electronic user interface as a scanning interface that sequentially highlights a plurality of the electronic control switches in interaction cycles;compute, over a rolling window of interaction cycles, a selection strike rate as a ratio of (i) a sum of scoring weights for interaction cycles in which a selection occurred to (ii) a sum of opportunity weights for interaction cycles in the rolling window, wherein opportunity weights of the sum of opportunity weights are based at least in part on a rest factor assigned to nonselected electronic control switches and scoring weights of the sum of scoring weights are based at least in part on a bonus factor that increases credit for selections made in longer interaction cycles;compute a pacing index based at least in part on a ratio of the selection strike rate relative to a baseline selection strike rate for the user; anddetermine that the base arrangement exceeds the capability of the user when the pacing index is below a threshold.

294. A non-transitory computer-readable medium storing code, the code comprising instructions executable by one or more processors to:provide a display on an electronic user interface operative with a brain-computer interface, wherein the display comprises a plurality of electronic control switches selectable using a neural activity of a user, and wherein the electronic user interface can adjust a complexity level of the display among a plurality of interface tiers including a highest interface tier;determine whether the user is able to interact with the electronic user interface at the highest interface tier across a threshold quantity of sessions; andgenerate a graduation indicator in response to determining that the user is able to interact with the electronic user interface at the highest interface tier across the threshold quantity of sessions, wherein the graduation indicator indicates a recommendation for the user to transition to a non-adapting user interface that operates without complexity adjustment based on an ability level of the user.

295. The non-transitory computer-readable medium of claim 294, wherein the threshold quantity of sessions comprises a predetermined quantity of consecutive sessions in which the user has consistently interacted with the electronic user interface at the highest interface tier.

296. The non-transitory computer-readable medium of any of claims 294 through 295, wherein, to determine whether the user has interacted with the electronic user interface at the highest interface tier, the instructions are executable by the one or more processors to: determine that at least one of a response time, an accuracy, a reproducibility of theAttorney Docket No.: SYNC-N-Z054-00-WOneural activity, or an error rate associated with interaction at the highest interface tier meets or exceeds a performance threshold across the threshold quantity of sessions.

297. The non-transitory computer-readable medium of any of claims 294 through 296, wherein the instructions are further executable by the one or more processors to:transmit the graduation indicator to at least one of a caregiver or a clinician associated with the user.

298. The non-transitory computer-readable medium of any of claims 294 through 297, wherein:the plurality of interface tiers comprises at least a binary-choice interface tier, a keyboard interface tier, and the highest interface tier, andthe highest interface tier corresponds to a full-complexity interface.

299. The non-transitory computer-readable medium of any of claims 294 through 298, wherein the instructions are further executable by the one or more processors to:generate a consistency score based on an interaction of the user with the electronic user interface at the highest interface tier across a plurality of sessions, wherein generating the graduation indicator is triggered when the consistency score exceeds a graduation threshold.

300. The non-transitory computer-readable medium of any of claims 294 through 299, wherein the graduation indicator comprises at least one of a visual notification displayed on the electronic user interface or an auditory notification.

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