Systems and methods for general control using neural signals

Abstract

The invention discloses a system and method for general control using neural signals. Universal switch modules, universal switches, and methods of using the same are disclosed, including methods of preparing an individual to interface with an electronic device or software. For example, a method is disclosed that may include measuring a brain-related signal of an individual to obtain a first sensed brain-related signal when the individual generates a task-independent idea. The method may include transmitting a first sensed brain-related signal to a processing unit. The method may include associating a task-independent idea and a first sensed brain-related signal with N input commands. The method may include compiling the task-independent idea, the first sensed brain-related signal, and the N input commands into an electronic database.

Description

[0001] This application is a divisional application of an application with an application date of May 14, 2020, application number 202080050868.6, and invention name “System and method for general control using neural signals”.

[0002] CROSS-REFERENCE TO RELATED APPLICATIONS

[0003] This application is a continuation of U.S. Patent Application No. 16 / 457,493, filed on June 28, 2019, which claims priority to U.S. Provisional Application No. 62 / 847,737, filed on May 14, 2019, each of which is incorporated herein by reference in its entirety for all purposes. background 1. Technical field:

[0005] The present disclosure relates generally to methods of using neural-related signals, and more particularly to methods of using neural signals as universal switches. 2. Technical background:

[0006] Currently, for brain-computer interfaces (BCIs), users are required to either perform task-related mental tasks to perform a given target task (e.g., try to move a cursor when the target task is to move the cursor), or to perform task-independent mental tasks to perform a given target task (e.g., try to move your hand to move the cursor to the right). In addition, current BCIs only allow users to use thoughts (e.g., task-related mental tasks or task-independent mental tasks) to control predefined target tasks set by researchers. The present disclosure describes novel methods and systems that enable and allow BCI users to independently control various terminal applications, including software and devices, using given task-independent thoughts.

[0007] Brief Summary of the Invention

[0008] Control systems and methods using neural-related signals are disclosed, including universal switches and methods of using the same.

[0009] Methods of preparing an individual to interface with an electronic device or software are disclosed. For example, a method is disclosed that may include measuring a neural-related signal of the individual to obtain a first sensed neural signal when the individual generates a first task-irrelevant thought. The method may include transmitting the first sensed neural signal to a processing unit. The method may include associating the first task-irrelevant thought and the first sensed neural signal with a first input command. The method may include compiling the first task-irrelevant thought, the first sensed neural signal, and the first input command into an electronic database.

[0010] A method of controlling a first device and a second device is disclosed. For example, a method is disclosed that may include measuring a neural-related signal of an individual to obtain a sensed neural signal when the individual generates a task-irrelevant thought. The method may include transmitting the sensed neural signal to a processor. The method may include associating the sensed neural signal with a first device input command and a second device input command via the processor. The method may include, when associating the sensed neural signal with the first device input command and the second device input command, electrically transmitting the first device input command to the first device or electrically transmitting the second device input command to the second device.

[0011] A method for preparing an individual to interface with a first device and a second device is disclosed. For example, a method is disclosed that may include measuring a brain-related signal of the individual to obtain a sensed brain-related signal when the individual generates a task-specific thought by thinking of a first task. The method may include transmitting the sensed brain-related signal to a processing unit. The method may include associating the sensed brain-related signal with a first device input command associated with a first device task via the processing unit. The first device task is different from the first task. The method may include associating the sensed brain-related signal with a second device input command associated with a second device task via the processing unit. The second device task is different from the first device task and the first task. The method may include, when associating the sensed brain-related signal with the first device input command and the second device input command, electrically transmitting the first device input command to the first device to perform the first device task associated with the first device input command, or electrically transmitting the second device input command to the second device to perform the second device task associated with the second device input command.

[0012] A method for preparing an individual for connection to an electronic device or software interface is disclosed, the method comprising:

[0013] When the individual generates a first task-irrelevant thought, measuring a neural-related signal of the individual to obtain a first sensed neural signal;

[0014] transmitting the first sensed neural signal to a processing unit;

[0015] associating the first task-irrelevant thought and the first sensory neural signal with the first input command; and

[0016] The first task-irrelevant thought, the first sensory neural signal, and the first input command are compiled into an electronic database.

[0017] In one embodiment, the first input command is an input command of a first terminal application.

[0018] In an embodiment, the method further comprises associating the first task-irrelevant thought and the first sensed neural signal with a second input command.

[0019] In one embodiment, the second input command is an input command of a second terminal application.

[0020] In one embodiment, the method further comprises controlling the first terminal application with a first input command when the first sensed neural signal is detected.

[0021] In one embodiment, the method further comprises controlling a second terminal application with a second input command when the first sensed neural signal is detected.

[0022] In one embodiment, the method further comprises compiling the first task-irrelevant thought, the first sensed neural signal, and the second input command into an electronic database.

[0023] In one embodiment, the first sensed neural signal is a first sensed brain electrical activity.

[0024] In one embodiment, measuring the nerve-related signal of the individual includes measuring the nerve-related signal of the individual using an implantable intravascular device.

[0025] In one embodiment, the method further comprises monitoring the individual for a first sensed neural signal, and upon detecting the first sensed neural signal, electronically transmitting a first input command to the first end application or to the second end application.

[0026] In one embodiment, the method further includes monitoring the individual for a first sensed neural signal, and upon detecting the first sensed neural signal, electronically transmitting a first input command to the first end application and to the second end application.

[0027] In one embodiment, the method further comprises:

[0028] When the individual generates a second task-irrelevant thought, measuring a neural correlation signal of the individual to obtain a second sensory neural signal;

[0029] transmitting the second sensed neural signal to a processing unit;

[0030] Associating the second task-irrelevant thought and the second sensed neural signal with a third input command, wherein the third input command is an input command of the first terminal application, the second terminal application, or the third terminal application;

[0031] compiling the second task-irrelevant thought, the second sensory neural signal, and the third input command into an electronic database; and

[0032] When the second sensed neural signal is detected, a third input command is electrically transmitted to the first end application, the second end application, or the third end application.

[0033] A method for controlling a first device and a second device is disclosed, the method comprising:

[0034] Measuring the neural correlates of the individual to obtain a sensed neural signature when the individual generates task-irrelevant thoughts;

[0035] transmitting the sensed neural signals to a processor;

[0036] associating, via the processor, the sensed neural signal with the first device input command and the second device input command; and

[0037] When the sensed neural signal is associated with the first device input command and the second device input command, the first device input command is electrically transmitted to the first device or the second device input command is electrically transmitted to the second device.

[0038] In one embodiment, the method further includes electrically transmitting the first device input command to the first device and electrically transmitting the second device input command to the second device when associating the sensed neural signal with the first device input command and the second device input command.

[0039] In one embodiment, the method further comprises compiling the task-irrelevant thoughts, the first sensory neural signal, and the first input command into an electronic database.

[0040] In one embodiment, the method further comprises compiling the task-irrelevant thoughts, the sensed neural signals, the first device input command, and the second device input command into an electronic database.

[0041] In one embodiment, sensing the neural signal is sensing brain electrical activity.

[0042] In one embodiment, measuring the nerve-related signal of the individual includes measuring the nerve-related signal of the individual using an implantable intravascular device.

[0043] A method for preparing an individual to interface with a first device and a second device is disclosed, the method comprising:

[0044] measuring a brain-related signal of the individual to obtain a sensed brain-related signal when the individual generates a task-specific thought by thinking of a first task;

[0045] transmitting the sensed brain-related signals to a processing unit;

[0046] associating, via the processing unit, the sensed brain-related signal with a first device input command associated with a first device task, wherein the first device task is different from the first task;

[0047] associating, via the processing unit, the sensed brain-related signal with a second device input command associated with a second device task, wherein the second device task is different from the first device task and the first task; and

[0048] When associating the sensed brain-related signal with a first device input command and a second device input command, the first device input command is electrically transmitted to the first device to perform a first device task associated with the first device input command, or the second device input command is electrically transmitted to the second device to perform a second device task associated with the second device input command.

[0049] In one embodiment, the method also includes, when associating the sensed brain-related signal with the first device input command and the second device input command, electrically transmitting the first device input command to the first device to perform a first device task associated with the first device input command, and electrically transmitting the second device input command to the second device to perform a second device task associated with the second device input command. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The drawings shown and described are exemplary embodiments and are non-limiting. The same reference numerals indicate identical or functionally equivalent features throughout.

[0052] Figure 1A A variation of a generic switch module is shown.

[0053] Figure 1B shows that when a patient thinks of a thought, Figure 1A A variation of the general switch module.

[0054] Figure 1C Shows Figure 1A and Figure 1B A variation of the user interface of a host device of the universal switch module.

[0055] Figure 2A-2D A variation of the general switch model that communicates with an end application is shown.

[0056] Figure 3 A variation of a wireless universal switch module that communicates with an end application is shown.

[0057] Figure 4 A variation of a generic switch module for recording nerve-related signals of a patient is shown.

[0058] Figure 5 Shown by Figure 1A-Figure 1C A variation of the approach taken by the generic switch module.

[0059] Figure 6 Shown by Figure 1A-Figure 1C A variation of the approach taken by the generic switch module.

[0060] Figure 7 Shown by Figure 1A-Figure 1C A variation of the approach taken by the generic switch module. Detailed Description

[0062] A universal switch module, a universal switch and a method of using the same are disclosed. For example, Figure 1A-Figure 1C A variation of a universal switch module 10 is shown, and a patient 8 (e.g., a BCI user) can use the universal switch module 10 to control one or more terminal applications 12 by thinking of a thought 9. The module 10 may include a neural interface 14 and a host device 16. The module 10 (e.g., the host device 16) may communicate with one or more terminal applications 12 by wire and / or wireless communication. The neural interface 14 may be a biological medium signal detector (e.g., an electrical conductor, a biochemical sensor), the host device 16 may be a computer (e.g., a laptop, a smartphone), and the terminal application 12 may be any electronic device or software. The neural interface 14 may monitor a neural-related signal 17 of a biological medium via one or more sensors. The processor of the module 10 may analyze the detected neural-related signal 17 to determine whether the detected neural-related signal 17 is associated with a thought 9 assigned to an input command 18 of the terminal application 12. When a thought 9 assigned to the input command 18 is detected by the neural interface 14 and associated with the input command 18 by the processor, the input command 18 may be sent (e.g., via a processor, a controller, or a transceiver) to the terminal application 12 associated with the input command 18. The idea 9 can be assigned to the input of the command 18 of multiple terminal applications 12. The module 10 thereby advantageously enables the patient 8 to independently control multiple terminal applications 12 (e.g., a first terminal application and a second terminal application) with a single idea (e.g., idea 9), wherein the idea 9 can be used to control the first application and the second application at different times and / or simultaneously. In this way, the module 10 can be used as a universal switch module, capable of controlling multiple terminal applications 12 (e.g., software and devices) using the same idea 9. The idea 9 can be a universal switch that can be assigned to any input command 18 of any terminal application 12 (e.g., an input command 18 of a first terminal application and an input command 18 of a second terminal application). The first terminal application can be a first device or a first software. The second terminal application can be a second device or a second software.

[0063] When the patient 8 thinks of the thought 9, the input commands 18 associated with the thought 9 can be sent by the module 10 (e.g., via a processor, controller, or transceiver) to their corresponding terminal applications 12. For example, if the thought 9 is assigned to the input command 18 of the first terminal application, then when the patient 8 thinks of the thought 9, the input command 18 of the first terminal application can be sent to the first terminal application, and if the thought 9 is assigned to the input command 18 of the second terminal application, then when the patient 8 thinks of the thought 9, the input command 18 of the second terminal application can be sent to the second terminal application. The thought 9 can thus interface with or control multiple terminal applications 12, so that the thought 9 can work like a universal button (e.g., thought 9) on a universal controller (e.g., the patient's brain). Any number of thoughts 9 can be used as switches. The number of thoughts 9 used as switches can correspond to, for example, the number of controls (e.g., input commands 18) required or desired to control the terminal applications 12.

[0064] Using a video game controller as an example, the patient's thoughts 9 can be assigned to any input command 18 associated with any single button, any combination of buttons, and any directional movement of the controller (e.g., of a joystick, a control pad (such as a directional pad)), so that the patient 8 can use their thoughts 9 to play any game of any video game system with or without the presence of a conventional physical controller. A video game system is just one example of a terminal application 12. Module 10 enables thoughts 9 to be assigned to input commands 18 of any terminal application 12, so that the patient's thoughts 9 can be mapped to controls of any software or device. Module 10 can thereby organize the patient's thoughts 9 into a set of assignable switches that are generic in nature, but specific in execution once assigned to an input command 18. Other illustrative examples of terminal applications 12 include mobile devices (e.g., vehicles, wheelchairs, wheelchair lifts), prostheses (e.g., prosthetic arms, prosthetic legs), phones (e.g., smartphones), smart home appliances, and smart home systems.

[0065] The neural interface 14 can detect neural-related signals 17, including signals associated with the thought 9 and signals not associated with the thought 9. For example, the neural interface 14 can have one or more sensors that can detect (also referred to as obtain, sense, record, and measure) neural-related signals 17, including signals generated by the biological media of the patient 8 when the patient 8 thinks of the thought 9, and including signals generated by the biological media of the patient 8 that are not associated with the thought 9 (e.g., forming the patient's response to a stimulus not associated with the thought 9). The sensors of the neural interface 14 can record signals from the biological media of the patient 8 and / or stimulate the biological media of the patient 8. The biological media can be, for example, neural tissue, vascular tissue, blood, bone, muscle, cerebrospinal fluid, or any combination thereof. The sensor can be, for example, an electrode, wherein the electrode can be any electrical conductor for sensing the electrical activity of the biological media. The sensor can be, for example, a biochemical sensor. The neural interface 14 can have a single type of sensor (e.g., only an electrode) or multiple types of sensors (e.g., one or more electrodes and one or more biochemical sensors).

[0066] The neural-related signal may be any signal detectable from a biological medium (e.g., an electrical signal, a biochemical signal), may be any feature or features extracted from a detected neural-related signal (e.g., via a computer processor), or both, wherein the extracted feature may be or may include feature information about the patient's 8 thoughts 9, such that different thoughts 9 may be distinguished from one another. As another example, the neural-related signal may be an electrical signal, may be any signal caused by an electrical signal (e.g., a biochemical signal), may be any feature or features extracted from a detected neural-related signal (e.g., via a computer processor), or any combination thereof. The neural-related signal may be a neural signal such as a brain wave. When the biological medium is within the patient's skull, the neural-related signal may be, for example, a brain signal (e.g., detected from brain tissue) that is generated or caused by the patient 8 thinking of a thought 9. In this way, the neural-related signal may be a brain-related signal, such as an electrical signal from any part or parts of the patient's brain (e.g., motor cortex, sensory cortex). When the biological medium is outside the patient's skull, the neural-related signal can be, for example, an electrical signal associated with a muscle contraction (e.g., muscle contraction of a body part such as an eyelid, eye, nose, ear, finger, arm, toe, leg) that is generated or caused by the patient 8 thinking of a thought 9. The thought 9 (e.g., movement of a body part, memory, task) that the patient 8 thinks of when the neural-related signal is detected from the brain tissue of the patient 8 can be the same or different than the thought 9 that the patient 8 thinks of when the neural-related signal is detected from non-brain tissue. The neural interface 14 can be located inside the patient's brain, outside the patient's brain, or both.

[0067] The module 10 may include one or more neural interfaces 14, for example, 1 to 10 or more neural interfaces 14, including every 1 neural interface increment within the range (e.g., 1 neural interface, 2 neural interfaces, 10 neural interfaces), wherein each neural interface 14 may have one or more sensors (e.g., electrodes) configured to detect neural-related signals (e.g., neural signals). The location of the neural interface 14 may be selected to optimize the recording of neural-related signals, for example, such as selecting a location with the strongest signal, a location with the least interference from noise, a location where the neural interface 14 is implanted or joined to the patient 8 (e.g., via surgery) with the least trauma to the patient 8, or any combination thereof. For example, the neural interface 14 may be a brain-computer interface (such as an intravascular device (e.g., a stent)) having one or more electrodes for detecting brain electrical activity. In the case of using multiple neural interfaces 14, the neural interfaces 14 may be the same or different from each other. For example, where two neural interfaces 14 are used, both neural interfaces 14 may be intravascular devices having electrodes (e.g., an expandable and contractible stent having electrodes), or one of the neural interfaces 14 may be an intravascular device having electrodes, while the other of the two neural interfaces 14 may be a device having a sensor that is different from the intravascular device having electrodes.

[0068] Figure 1A and Figure 1B It is further shown that the module 10 may include a telemetry unit 22 adapted to communicate with the neural interface 14, and a communication conduit 24 (e.g., wires) to facilitate communication between the neural interface 14 and the telemetry unit 22. The host device 16 may be adapted to communicate with the telemetry unit 22 in wired and / or wireless communication. The host device 16 may communicate with the telemetry unit 22 in wired and / or wireless communication.

[0069] Figure 1A and Figure 1B It is further shown that the telemetry unit 22 may include an internal telemetry unit 22a and an external telemetry unit 22b. The internal telemetry unit 22a may communicate with the external telemetry unit 22b by wire or wirelessly. For example, the external telemetry unit 22b may be wirelessly connected to the internal telemetry unit 22a through the patient's skin. The internal telemetry unit 22a may communicate with the neural interface 14 by wire or wirelessly, and the neural interface 14 may be electrically connected to the internal telemetry unit 22a via a communication conduit 24. The communication conduit 24 may be, for example, a wire, such as a stent lead.

[0070] The module 10 may have a processor (also referred to as a processing unit) that may analyze and decode neural-related signals detected by the neural interface 14. The processor may be a computer processor (e.g., a microprocessor). The processor may apply a mathematical algorithm or model to detect neural-related signals corresponding to when the patient 8 generates a thought 9. For example, once the neural interface 14 senses a neural-related signal 17, the processor may apply a mathematical algorithm or a mathematical model to detect, decode, and / or classify the sensed neural-related signal 17. As another example, once the neural interface 14 senses a neural-related signal 17, the processor may apply a mathematical algorithm or a mathematical model to detect, decode, and / or classify information in the sensed neural-related signal 17. Once the neural-related signal 17 detected by the neural interface 14 is processed by the processor, the processor may associate the processed information (e.g., the detected, decoded, and / or classified neural-related signal 17 and / or the detected, decoded, and / or classified information of the sensed neural-related signal 17) with an input command 18 of the terminal application 12.

[0071] The neural interface 14, the host device 16, and / or the telemetry unit 22 may have a processor. As another example, the neural interface 14, the host device 16, and / or the telemetry unit 22 may have a processor (e.g., a processor as described above). For example, the host device 16 may analyze and decode the neural-related signals 17 detected by the neural interface 14 via the processor. The neural interface 14 may communicate with the host device 16 in wired or wireless communication, and the host device 16 may communicate with the terminal application 12 in wired or wireless communication. As another example, the neural interface 14 may communicate with the telemetry unit 22 in wired or wireless communication, the telemetry unit 22 may communicate with the host device 16 in wired or wireless communication, and the host device 16 may communicate with the terminal application 12 in wired or wireless communication. For example, data may be transferred from the neural interface 14 to the telemetry unit 22, from the telemetry unit 22 to the host device 16, from the host device 16 to one or more terminal applications 12, or any combination thereof, to detect thoughts 9 and trigger input commands 18. As another example, data can be transferred in the reverse order, e.g., from one or more terminal applications 12 to the host device 16, from the host device 16 to the telemetry unit 22, from the telemetry unit 22 to the neural interface 14, or any combination thereof, e.g., to stimulate a biological medium via one or more sensors. The data can be data collected or processed by the processor, including, for example, neural-related signals and / or features extracted therefrom. When the data flows, for example, from the processor to the sensor, the data can include stimulation instructions such that when the neural interface 14 processes the stimulation instructions, the sensor of the neural interface can stimulate the biological medium.

[0072] Figure 1A and Figure 1BIt is further shown that when patient 8 thinks of thought 9, biological media of patient 8 (e.g., biological media inside the skull, outside the skull, or both) can generate neural-related signals 17 detectable by neural interface 14. When patient 8 thinks of thought 9, sensors of neural interface 14 can detect neural-related signals 17 associated with thought 9. Neural-related signals 17 associated with thought 9, features extracted from these neural-related signals 17, or both can be assigned any input command 18 or associated with any input command 18 for any terminal application 12 controllable by universal switch module 10. Therefore, each of the detectable neural-related signals 17 and / or their extracted features can be advantageously used as a universal switch, assignable to any input command 18 of any terminal application 12. In this way, when neural interface 14 detects thought 9, input command 18 associated with the thought 9 can be triggered and sent to the terminal application 12 associated with the triggered input command 18.

[0073] For example, when the neural interface 14 detects the thought 9 (e.g., through the sensed neural-related signal 17), the processor may analyze (e.g., detect, decode, classify, or any combination thereof) the sensed neural-related signal 17 and associate the sensed neural-related signal 17 and / or features extracted therefrom with the corresponding assigned input command 18. The processor may thereby determine whether the thought 9 (e.g., the sensed neural-related signal 17 and / or features extracted therefrom) is associated with any input command 18. When it is determined that the thought 9 is associated with the input command 18, the processor or controller may activate (also referred to as trigger) the input command 18. Once the input command 18 is triggered by the module 10 (e.g., by the processor or controller of the host device 16), the triggered input command 18 may be sent to its corresponding terminal application 12, so that the terminal application 12 (e.g., a wheelchair, a prosthetic arm, a smart home appliance such as a coffee machine) may be controlled with the triggered input command 18. Once the terminal application 12 receives the triggered input command 18, the terminal application 12 can execute one or more instructions of the input command 18 (e.g., move the wheelchair forward at a speed of 1 meter per second, pinch the thumb and index finger of the prosthetic arm together, and turn on the smart coffee machine). Therefore, when it is determined that the thought 9 (e.g., the sensed neural-related signal 17 and / or the features extracted therefrom) is associated with the input command 18, the input command 18 can be sent to its corresponding terminal application 12.

[0074] The extracted features can be components of the sensed neural-related signal 17, including, for example, voltage fluctuation patterns in the sensed neural-related signal 17, power fluctuations in a specific frequency band embedded in the sensed neural-related signal 17, or both. For example, the neural-related signal 17 can have different ranges of oscillation frequencies that correspond to the times when the patient 8 thinks of thoughts 9. The frequencies of a specific frequency band can contain specific information. For example, high-band frequencies (e.g., 65Hz–150Hz) can contain information associated with movement-related thoughts, and therefore, features in this high-band frequency range (e.g., extracted or identified from the sensed neural-related signal 17) can be used to classify and / or decode neural events (e.g., thoughts 9).

[0075] Thought 9 may be a universal switch. Thought 9 may function as (e.g., be used as) a universal switch, wherein thought 9 may be assigned to any input command 18 and vice versa. Thought 9 may be assigned to or associated with any input command 18 of any terminal application 12 controllable by the universal switch module 10 through a detectable neural-related signal 17 associated therewith and / or features extractable from the neural-related signal 17. Thought 9 may be assigned to or associated with any input command 18 of any terminal application 12 controllable by the universal switch module 10. The patient 8 may activate the desired input command 18 by thinking of the thought 9 associated with the patient's 8 desired input command 18. For example, when the neural interface 14 detects a thought 9 (e.g., a memory of the patient's 9th birthday party) assigned to a particular input command 18 (e.g., moving the wheelchair forward), the processor (e.g., of the host device 16) may associate the neural-related signal 17 associated with the thought (e.g., the memory of the 9th birthday party) and / or features extracted therefrom with the corresponding assigned input command 18 (e.g., moving the wheelchair forward). When the detected neural-related signal (e.g., and / or the extracted features associated therewith) is associated with an assigned input command 18, the host device 16 can send the input command 18 via a processor or controller to a terminal application 12 associated with the input command 18 to control the terminal application 12 using the input command 18, which is triggered by the patient 8 thinking of an idea 9.

[0076] In the case where the idea 9 is assigned to multiple terminal applications 12 and only one of the terminal applications 12 is active (e.g., powered on and / or running), the host device 16 may send a triggered input command 18 to the active terminal application 12. As another example, in the case where the idea 9 is assigned to multiple terminal applications 12 and some of the terminal applications 12 are active (e.g., powered on or running) and some of the terminal applications 12 are inactive (e.g., powered off or in standby mode), the host device 16 may send a triggered input command 18 to both the active and inactive terminal applications 12. When the input command 18 is received by the active terminal application 12, the active terminal application 12 may execute the input command 18. The inactive terminal application 12 may execute the input command 18 when the inactive application 12 becomes active (e.g., is powered on or starts running), or the input command 18 may be placed in a queue (e.g., by the module 16 or by the terminal application 12) to be executed when the inactive application 12 becomes active. As yet another example, where idea 9 is assigned to multiple terminal applications 12 and more than one of the terminal applications 12 is active (e.g., powered on and / or running) (e.g., a first terminal application and a second terminal application are active), host device 16 may send a triggered input command 18 associated with the first terminal application to the first terminal application, and may send a triggered input command 18 associated with the second terminal application to the second terminal application, or module 10 may give patient 8 a choice of which of the triggered input commands 18 patient 8 wants to send (e.g., only send a triggered input command 18 associated with the first terminal application, only send a triggered input command 18 associated with the second terminal application, or send both triggered input commands 18).

[0077] The idea 9 can be any idea or combination of ideas. For example, the idea 9 that the patient 8 thinks of can be a single idea, multiple ideas, multiple ideas in succession, multiple ideas at the same time, ideas with different durations, ideas with different frequencies, one or more sequential ideas, one or more combined ideas, or any combination thereof. The idea 9 can be a task-related idea, a task-independent idea, or both, wherein the task-related idea is related to the expected task of the patient 8, and the task-independent idea is independent of the expected task of the patient 8. For example, the idea 9 can be of a first task, and the patient 8 can think of the first task to complete the second task (also referred to as the expected task and the target task), for example, by using the module 10. The first task can be the same as or different from the second task. When the first task is the same as the second task, the idea 9 can be a task-related idea. In the case where the first task is different from the second task, the idea 9 can be a task-independent idea. For example, in the case where the first task that the patient 8 thinks of is to move a limb (e.g., an arm, a leg) and the second task is the same as the first task, that is, to move a limb (e.g., an arm, a leg) such as a prosthetic limb, the idea 9 (e.g., of the first task) can be a task-related idea. The prosthetic limb can be, for example, a terminal application 12 that the patient 8 controls using the idea 9. For example, for task-related thoughts, when the target task is to move the cursor, the patient 8 can think of moving the cursor. In contrast, for task-independent thoughts 9, where the patient 8 thinks of moving a limb (e.g., an arm) as a first task, the second task can be any task different from the first task of moving a limb (e.g., an arm), so that the second task can be a task of any terminal application 12 different from the first task. For example, for task-independent thoughts, when the target task is to move the cursor to the right, the patient 8 can think of moving a body part (e.g., their hand) to the right. The patient 8 can therefore think of the first task (e.g., thought 9) to complete any second task, where the second task can be the same as or different from the first task. The second task can be any task of any terminal application 12. For example, the second task can be any input command 18 of any terminal application 12. Thought 9 (e.g., the first task) can be assignable to any second task. Thought 9 (e.g., the first task) can be assigned to any second task. The patient 8 can thus think of the first task of triggering any input command 18 (e.g., any second task) of any terminal application 12. Therefore, the first task can be advantageously used as a universal switch. Each thought 9 may generate a repeatable neural-related signal (e.g., detectable neural-related signal 17) detectable by neural interface 14. Each detectable neural-related signal and / or feature extractable therefrom may be a switch. For example, a switch may be activated (also referred to as being triggered) when patient 8 thinks of thought 9 and a sensor detects that a switch is activated and / or a processor determines that one or more features extracted from the detected neural-related signal are present.The switch may be a general switch that may be assigned and reassigned to any input command 18, e.g., any set of input commands. An input command 18 may be added to, removed from, and / or modified in any set of input commands. For example, each terminal application 12 may have a set of input commands 18 associated therewith, to which the neural-related signal 17 of the thought 9 may be assigned.

[0078] Some thoughts 9 may be task-irrelevant thoughts (e.g., patient 8 attempts to move their hand to move a cursor to the right), some thoughts 9 may be task-related thoughts (e.g., patient 8 attempts to move a cursor when the target task is to move a cursor), some thoughts 9 may be both task-irrelevant thoughts and task-related thoughts, or any combination thereof. In the case where thought 9 is both a task-irrelevant thought and a task-related thought, thought 9 may function as both a task-irrelevant thought (e.g., patient 8 attempts to move their hand to move a cursor to the right) and as a task-related thought (e.g., patient attempts to move a cursor when the target task is to move a cursor), such that thought 9 may be associated with a plurality of input commands 18, wherein one or more of these input commands 18 may be task-related to thought 9, and wherein one or more of these input commands 18 may be task-irrelevant to thought 9.

[0079] In this way, the idea 9 can be a universal switch that can be assigned to any input command 18 of any terminal application 12, where each idea 9 can be assigned to one or more terminal applications 12. The module 10 advantageously enables each patient 8 to use their idea 9 like buttons on a controller (e.g., video game controller, any control interface) to control any terminal application 12 that the patient 8 wants to control. For example, an idea 9 can be assigned to each input command 18 of a terminal application 12, and the assigned input commands 18 can be used in any combination, like buttons on a controller, to control the terminal application 12. For example, in the case where the terminal application 12 has four input commands 18 (e.g., like four buttons on a controller—a first input command, a second input command, a third input command, and a fourth input command), a different thought 9 may be assigned to each of the four input commands 18 (e.g., a first thought 9 may be assigned to the first input command 18, a second thought 9 may be assigned to the second input command 18, a third thought 9 may be assigned to the third input command 18, and a fourth thought 9 may be assigned to the fourth input command 18), so that the patient 8 may use the four thoughts 9 to activate the four input commands 18 and combinations thereof (e.g., any order, number, frequency, and duration of the four input commands 18) to control the terminal application 12. For example, for a terminal application 12 having four input commands 18, the four input commands 18 may be used to control the terminal application 12 using any combination of the four thoughts 9 assigned to the first, second, third, and fourth input commands 18, including, for example, a single activation of each input command itself, multiple activations of each input command itself (e.g., two activations of less than 5 seconds, three activations of less than 10 seconds), a combination of multiple input commands 18 (e.g., simultaneous or consecutive first and second input commands), or any combination thereof. Like each individual idea 9, each combination of ideas 9 can act as a universal switch. The patient 8 can control multiple terminal applications 12 with the first, second, third, and fourth ideas 9. For example, the first idea 9 can be assigned to the first input command 18 of the first terminal application 12, the first idea 9 can be assigned to the first input command 18 of the second terminal application 12, the second idea 9 can be assigned to the second input command 18 of the first terminal application 12, the second idea 9 can be assigned to the second input command 18 of the second terminal application 12, the third idea 9 can be assigned to the third input command 18 of the first terminal application 12, the third idea 9 can be assigned to the third input command 18 of the second terminal application 12, the fourth idea 9 can be assigned to the fourth input command 18 of the first terminal application 12, the fourth idea 9 can be assigned to the fourth input command 18 of the second terminal application 12, or any combination thereof.For example, the first idea 9 may be assigned to the first input command 18 of the first terminal application 12 and the first input command 18 of the second terminal application 12, the second idea 9 may be assigned to the second input command 18 of the first terminal application 12 and the second input command 18 of the second terminal application 12, the third idea 9 may be assigned to the third input command 18 of the first terminal application 12 and the third input command 18 of the second terminal application 12, the fourth idea 9 may be assigned to the fourth input command 18 of the first terminal application 12 and the fourth input command 18 of the second terminal application 12, or any combination thereof. The first, second, third, and fourth ideas 9 may be assigned to any application 12 (e.g., the first and second terminal applications). Some ideas may be assigned to only a single application 12, while some ideas may be assigned to multiple applications 12. Even in the case where an idea 9 is assigned to only a single application 12, an idea assigned to only one application 12 may be assigned to multiple applications 12, so that the patient 8 can utilize the universal applicability of the idea 9 (e.g., assigned to only one terminal application 12) as needed or desired. As another example, all ideas 9 may be assigned to multiple terminal applications 12.

[0080] The functionality of each input command 18 or combination of input commands for the terminal application 12 may be defined by the patient 8. As another example, the functionality of each input command 18 or combination of input commands for the terminal application 12 may be defined by the terminal application 12 such that a third party may plug in and make their terminal application's input commands 18 assignable (also referred to as mappable) to a set or subset of repeatable ideas 9 of a patient. This may advantageously allow the third party program to be more easily accessible and customized to the different desires, needs, and capabilities of different patients 8. The module 10 may advantageously be an application programming interface (API) that a third party may interface with, and allow the patient's 8 ideas 9 to be assigned and reassigned to various input commands 18, wherein, as described herein, each input command 18 may be activated by the patient 8 thinking of the idea 9 assigned to the input command 18 that the patient 8 wants to activate.

[0081] The patient's thoughts 9 can be assigned to input commands 18 of the terminal application 12 via a person (e.g., the patient or another person), a computer, or both. For example, the patient's 8 thoughts 9 (e.g., detectable neural-related signals and / or extractable features associated with the thoughts 9) can be assigned to the input commands 18 by the patient 8, can be assigned by a computer algorithm (e.g., based on the signal strength of the detectable neural-related signals associated with the thoughts 9), can be changed by the patient 8 (e.g., reassigned), can be changed by the algorithm (e.g., based on the relative signal strength of the switches or the availability of new repeatable thoughts 9), or any combination thereof. The input commands 18 and / or functions associated with the input commands 18 can be, but need not be, independent of the thoughts 9 associated with activating the input commands 18. For example, Figure 1A-Figure 1C An exemplary variation of a non-specific or generic mode switching program (e.g., an application programming interface (API)) that a third party may insert is shown, which allows thoughts 9 (e.g., detectable neural-related signals and / or extractable features associated with thoughts 9) to be assigned and reassigned to various input commands 18. By assigning input commands 18, thoughts 9 are assigned, and vice versa, the patient 8 can use the same thought 9 for various input commands 18 in the same or different terminal applications 12. Similarly, by reassigning input commands 18, thoughts 9 are assigned, and vice versa, the patient 8 can use the same thought 9 for various input commands 18 in the same or different terminal applications 12. For example, a thought 9 assigned to an input command 18 that causes a prosthetic hand (e.g., a first terminal application) to open can be assigned to a different input command 18 that causes a cursor (e.g., a second terminal application) to do something on a computer (e.g., any function associated with a cursor associated with a mouse or touchpad of a computer, including, for example, movement of the cursor and selection using the cursor, such as left-click and right-click).

[0082] Figure 1A-Figure 1C It is further shown that the patient's 8 thoughts 9 can be assigned to multiple terminal applications 12, so that the patient 8 can switch between multiple terminal applications 12 without having to reassign input commands 18 each time the patient 8 uses a different terminal application 12. For example, thoughts 9 can be assigned to multiple terminal applications 12 at the same time (e.g., assigned to a first terminal application and a second terminal application, wherein the process of assigning thoughts 9 to both the first and second terminal applications can but need not occur simultaneously). Therefore, the patient's thoughts 9 can advantageously control any terminal application 12, including, for example, external gaming devices or various household appliances and devices (e.g., light switches, appliances, locks, thermostats, security systems, garage doors, windows, curtains, including any smart devices or systems, etc.). The neural interface 14 can thereby detect neural-related signals 17 (e.g., brain signals) that are unrelated to the functional tasks associated with the input commands 18 of the terminal application 12, wherein the terminal application 12 can be any electronic device or software, including devices inside and / or outside the patient's body. As another example, the neural interface 14 can thereby detect neural-related signals 17 (e.g., brain signals) associated with a functional task associated with an input command 18 of a terminal application 12, where the terminal application 12 can be any electronic device or software, including devices inside and / or outside the patient's body. As yet another example, the neural interface 14 can thereby detect neural-related signals 17 (e.g., brain signals) associated with task-related thoughts, task-irrelevant thoughts, or both task-related and task-irrelevant thoughts.

[0083] Some thoughts 9 may be task-irrelevant thoughts (e.g., patient 8 attempts to move their hand to move a cursor to the right), some thoughts 9 may be task-related thoughts (e.g., patient 8 attempts to move a cursor when the target task is to move a cursor), some thoughts 9 may be both task-irrelevant thoughts and task-related thoughts, or any combination thereof. In the case where thought 9 is both a task-irrelevant thought and a task-related thought, thought 9 may function as both a task-irrelevant thought (e.g., patient 8 attempts to move their hand to move a cursor to the right) and as a task-related thought (e.g., patient attempts to move a cursor when the target task is to move a cursor), such that thought 9 may be associated with multiple input commands 18, wherein one or more of these input commands 18 may be thought 9 task-related, and wherein one or more of these input commands 18 may be thought 9 task-irrelevant. As another example, all thoughts 9 may be task-irrelevant thoughts. Task-independent thoughts 9 and / or thoughts 9 used by the patient 8 as task-independent thoughts (e.g., thoughts 9 assigned to input commands 18 that are independent of thoughts 9) enable the patient 8 (e.g., a BCI user) to independently control various terminal applications 12, including software and devices, using a given task-independent thought (e.g., thought 9).

[0084] Figure 1A-Figure 1CIt is shown that, for example, patient 8 can think about idea 9 (e.g., with or without being asked to think about idea 9), and then rest. This task of thinking about idea 9 can generate a detectable neural-related signal corresponding to the idea 9 that the patient is thinking about. The task of thinking about idea 9 and then resting can be performed once, for example, when patient 8 thinks of idea 9 to control terminal application 12. As another example, the task of thinking about idea 9 can be repeated multiple times, for example, when patient 8 controls terminal application 12 by thinking about idea 9, or when the patient is training how to use idea 9 to control terminal application 12. When recording neural-related signals (e.g., brain-related signals) such as neural signals, features can be extracted (e.g., spectral power / time-frequency domain) or identified from the signal itself (e.g., time domain signal). These features can contain characteristic information about idea 9, and can be used to identify idea 9, distinguish multiple ideas 9 from each other, or both. As another example, these features can be used to formulate or train a mathematical model or algorithm that can use machine learning methods and other methods to predict the type of thought that generates neural signals. Using the algorithm and / or model, it is possible to predict in real time what the patient 8 is thinking, and the prediction can be associated with any desired input command 18. The process of the patient 8 thinking the same thought 9 can be repeated, for example, until the prediction provided by the algorithm and / or model matches the patient 8's thought 9. In this way, the patient 8 can calibrate each of their thoughts 9 that they will use to control the terminal application 12 so that each thought 9 assigned to the input command 18 generates a repeatable neural-related signal detectable by the neural interface 14. The algorithm can provide feedback 19 to the patient 8 on whether the prediction matches the actual thought 9 they should be thinking, where the feedback can be visual, auditory and / or tactile, which can induce the patient 8 to learn by trial and error. Machine learning methods and mathematical algorithms can be used to classify thoughts 9 based on features extracted and / or identified from the sensed neural-related signals 17. For example, a training data set can be recorded in which the patient 8 rests and thinks multiple times, the processor can extract relevant features from the sensed neural-related signals 17, and the parameters and hyperparameters of the mathematical model or algorithm used to distinguish between rest and thinking based on this data can be optimized to predict real-time signals. The same mathematical model or algorithm that has been tuned to predict real-time signals then advantageously allows the module 10 to convert the idea 9 into a real-time universal switch.

[0085] Figure 1A It is further shown that the neural interface 14 can monitor a biological medium (eg, the brain), such as electrical signals from the tissue being monitored (eg, neural tissue). Figure 1AIt is further shown that the neural-related signal 17 can be a brain-related signal. The brain-related signal can be, for example, an electrical signal from any part or parts of the patient's brain (e.g., motor cortex, sensory cortex). As another example, the brain-related signal can be any signal detectable in the skull (e.g., electrical, biochemical), can be any feature or features extracted from the detected brain-related signal (e.g., via a computer processor), or both. As yet another example, the brain-related signal can be an electrical signal, can be any signal caused by an electrical signal (e.g., a biochemical signal), can be any feature or features extracted from the detected brain-related signal (e.g., via a computer processor), or any combination thereof.

[0086] Figure 1A It is further shown that the terminal application 12 can be separated from the module 10, but has wired or wireless communication with the module 10. As another example, the module 10 (e.g., the host device 16) can be permanently or removably attached to or attachable to the terminal application 12. For example, the host device 16 can be removably docked with the application 12 (e.g., a device with software that the module 10 can communicate with). The host device 16 can have a port that can be engaged with the application 12, and vice versa. The port can be a charging port, a data port, or both. For example, in the case where the host device is a smartphone, the port can be a lightning transmission port. As another example, the host device 16 can have a tethered connection with the application 12, such as using a cable. The cable can be a power cable, a data transmission cable, or both.

[0087] Figure 1B It is further shown that when the patient 8 thinks of the thought 9 , the neural-related signal 17 may be a brain-related signal corresponding to the thought 9 . Figure 1B It is further shown that the host device 16 can have a processor (e.g., a microprocessor) that analyzes (e.g., detects, decodes, classifies, or any combination thereof) the neural-related signal 17 received from the neural interface 14, associates the neural-related signal 17 received from the neural interface 14 with its corresponding input command 18, associates features extracted from (e.g., spectral power / time-frequency domain) or identified in the neural-related signal 17 itself received from the neural interface 14 (e.g., time domain signal) with its corresponding input command 18, saves the neural-related signal 17 received from the neural interface 14, saves signal analysis (e.g., features extracted or identified from the neural-related signal 17), saves the association of the neural-related signal 17 with the input command 18, saves the association of features extracted or identified from the neural-related signal 17 with the input command 18, or any combination thereof.

[0088] Figure 1BIt is further shown that the host device 16 can have a memory. The data saved by the processor can be stored locally in the memory, can be stored on a server (e.g., on the cloud), or both. IDEA 9 and the data generated therefrom (e.g., detected neural-related signals 17, extracted features, or both) can be used as a reference library. For example, once IDEA 9 is calibrated, the neural-related signals 17 associated with the calibrated IDEA and / or its signature (also referred to as extracted) features can be saved. For example, when the neural interface 14 detects a neural-related signal 17, the IDEA 9 can be considered calibrated when the neural-related signal 17 and / or the features extracted therefrom have a repeatable signature or feature that is recognizable by the processor. The neural-related signals that are monitored and detected in real time can then be compared to this real-time stored calibration data. Whenever the detected signal 17 and / or one of its extracted features matches the calibration signal, the corresponding input command 18 associated with the calibration signal can be sent to the corresponding terminal application 12. For example, Figure 1A and Figure 1B It is shown that the patient 8 can be trained to use the module 10 by calibrating the neural related signals 17 associated with his thoughts 9 and storing these calibrations in a reference library. The training can provide feedback 19 to the patient 8.

[0089] Figure 1C Further shown is an exemplary user interface 20 of host device 16. User interface 20 may be a computer screen (eg, touch screen, non-touch screen). Figure 1CAn exemplary display of a user interface 20 is shown, including selectable systems 13, selectable input commands 18, and selectable terminal applications 12. A system 13 may be a grouping of one or more terminal applications 12. A system 13 may be added to and removed from a host device 16. A terminal application 12 may be added to and removed from a host device 16. A terminal application 12 may be added to and removed from a host device 16. A terminal application 12 may be added to and removed from a system 13. Each system 13 may have a corresponding set of input commands 18, which may be assigned to a corresponding set of terminal applications 12. As another example, the user interface 20 may display input commands 18 for each of the activated terminal applications 12 (e.g., a remote control). As yet another example, the user interface 20 may display input commands 18 for activated terminal applications (e.g., a remote control) and / or for deactivated terminal applications 12 (e.g., a stimulation sleeve, a phone, a smart home device, a wheelchair). This advantageously allows the module 10 to control any terminal application 12. The user interface 20 allows ideas 9 to be easily assigned to various input commands 18 for multiple terminal applications 12. The system grouping of terminal applications (e.g., system 1 and system 2) advantageously allows the patient 8 to organize the terminal applications 12 together using the user interface 20. Ready-made systems 13 can be uploaded to the module and / or the patient 8 can create their own system 13. For example, the first system can have all terminal applications 12 associated with mobility used by the patient 8 (e.g., wheelchair, wheelchair lift). As another example, the second system can have all terminal applications 12 associated with prostheses used by the patient 8. As yet another example, the third system can have all terminal applications 12 associated with smart home appliances used by the patient 8. As yet another example, the fourth system can have all terminal applications 12 used by the patient 8, which are associated with software or devices used by the patient for his or her profession. The terminal application 12 can be in one or more systems 13. For example, the terminal application 12 (e.g., wheelchair) can be in system 1 and / or system 2. This organizational efficiency can make it easier for patients 8 to manage their terminal applications 12. The module 10 may have one or more systems 13, such as 1 to 1000 or more systems 13, including every increment of system 13 within the range (e.g., 1 system, 2 systems, 10 systems, 100 systems, 500 systems, 1000 systems, 1005 systems, 2000 systems). For example, Figure 1C It is shown that the module 10 can have a first system 13a (e.g., system 1) and a second system 13b (e.g., system 2). Figure 1C It is shown that the terminal applications 12 may be grouped into various systems 13 , each of which has one or more terminal applications 12 , but as another example, the user interface 20 may not group the terminal applications into systems 13 .

[0090] Figure 1C It is further shown that the host device 16 can be used to assign thoughts 9 to input commands 18. For example, thoughts 9, neural-related signals 17 associated with thoughts 9, extracted features of neural-related signals 17 associated with thoughts 9, or any combination thereof can be assigned to input commands 18 of the system 13, such as by selecting an input command 18 (e.g., a left arrow) and selecting from a drop-down menu displaying thoughts 9 and / or data associated therewith (e.g., neural-related signals 17 associated with thoughts 9, extracted features of neural-related signals 17 associated with thoughts 9, or both) that can be assigned to the selected input command 18. Figure 1C It is further shown that when the input command 18 is triggered by the thought 9 or data associated therewith, feedback (eg, visual, auditory, and / or tactile feedback) may be provided to the patient 8 . Figure 1C It is further shown that one or more terminal applications 12 can be activated and deactivated in the system 13. An activated terminal application 12 can be in a powered-on, powered-off, or standby state. An activated terminal application 12 can receive a triggering input command 18. A deactivated terminal application 12 can be in a powered-on, powered-off, or standby state. In one example, a deactivated terminal application 12 may not be controllable by the patient's 8 thoughts 9 unless the terminal application 12 is activated. Activating the terminal application 12 using the user interface 20 can power on the terminal application 12. Deactivating the terminal application 12 using the user interface 20 can power off the deactivated terminal application 12, or otherwise disengage the module 10 from the deactivated terminal application 12 so that the processor does not associate the neural-related signal 17 with the thought 9 assigned to the deactivated terminal application 12. For example, Figure 1C An exemplary system 1 with five terminal applications 12 is shown, wherein the five terminal applications include five devices (e.g., remote control, stimulation sleeve, phone, smart home device, wheelchair), wherein one device (e.g., remote control) is activated and the other devices are deactivated. Once "start" is selected (e.g., via icon 20a), the patient 8 can control the terminal application 12 of the system (e.g., system 1), which is activated (e.g., remote control) using an input command 18 associated with the terminal application 12 of the system 1. Figure 1C It is further shown that any changes made using the user interface 20 may be saved using a save icon 20b, and any changes made using the user interface 20 may be canceled using a cancel icon 20c. Figure 1C It is further shown that the terminal application 12 may be an electronic device.

[0091] Figures 1A-1CIt is shown that the same specific set of ideas 9 can be used to control multiple terminal applications 12 (e.g., multiple terminal devices), making module 10 a universal switch module. Module 10 advantageously allows patients 8 (e.g., BCI users) to independently control various terminal applications 12, including, for example, multiple software and devices, using a given task-independent idea (e.g., idea 9). Module 10 can acquire neural-related signals (e.g., via neural interface 14), can decode the acquired neural-related signals (e.g., via a processor), can associate the acquired neural-related signals 17 and / or features extracted from these signals with corresponding input commands 18 of one or more terminal applications 12 (e.g., via a processor), and can control multiple terminal applications 12 (e.g., via module 10). Using module 10, idea 9 can be advantageously used to control multiple terminal applications 12. For example, module 10 can be used to control multiple terminal applications 12, where a single terminal application 12 can be controlled at a time. As another example, module 10 can be used to control multiple terminal applications simultaneously. Each idea 9 can be assigned to input commands 18 of multiple applications 12. In this way, the thoughts 9 can act as universal digital switches, where the module 10 can effectively reorganize the patient's motor cortex to represent digital switches, where each thought 9 can be a digital switch. These digital switches can be universal switches used by the patient 8 to control multiple terminal applications 12, because each switch can be assigned (e.g., via the module 10) to any input command 18 of the multiple terminal applications 12 (e.g., an input command of a first terminal application and an input command of a second terminal application). The module 10 can distinguish different thoughts 9 (e.g., different switches) via the processor.

[0092] The module 10 can interface with, for example, 1 to 1000 or more terminal applications 12, including every increment of terminal applications 12 within this range (e.g., 1 terminal application, 2 terminal applications, 10 terminal applications, 100 terminal applications, 500 terminal applications, 1000 terminal applications, 1005 terminal applications, 2000 terminal applications). For example, Figure 1C It is shown that the first system 13a can have a first terminal application 12a (e.g., a remote control), a second terminal application 12b (e.g., a stimulation sleeve), a third terminal application 12c (e.g., a phone), a fourth terminal application 12d (e.g., a smart home device), and a fifth terminal application 12e (e.g., a wheelchair).

[0093] Each terminal application may have, for example, 1 to 1000 or more input commands 18 that may be associated with the patient's 8 thoughts 9, or as another example, 1 to 500 or more input commands 18 that may be associated with the patient's 8 thoughts 9, or as yet another example, 1 to 100 or more input commands 18 that may be associated with the patient's 8 thoughts 9, including every 1 input command 18 within these ranges (e.g., 1 input command, 2 input commands, 10 input commands, 100 input commands, 500 input commands, 1000 input commands, 1005 input commands, 2000 input commands), and including any sub-ranges within these ranges (e.g., 1 to 25 or less input commands 18, 1 to 100 or less input commands 18, 25 to 1000 or less input commands 18), so that any number of input commands 18 may be triggered by the patient's thoughts 9, where the arbitrary number may be, for example, the number of input commands 18 to which the patient's 8 thoughts 9 are assigned. For example, Figure 1C An exemplary set of input commands 18 associated with an activated terminal application 12 (e.g., a first terminal application 12a) is shown, including a first terminal application first input command 18a (e.g., a left arrow), a first terminal application second input command 18b (e.g., a right arrow), and a first terminal application third input command 18c (e.g., enter). As another example, Figure 1C An exemplary set of input commands 18 associated with a deactivated terminal application 12 (e.g., second terminal application 12b) is shown, including a second terminal application first input command 18d (e.g., select output), where the second terminal application first input command 18d has not been selected, but may be any input command 18 of the second terminal application 12b. The first terminal application first input command 18a is also referred to as the first input command 18a of the first terminal application 12a. The first terminal application second input command 18b is also referred to as the second input command 18b of the first terminal application 12a. The first terminal application third input command 18c is also referred to as the third input command 18c of the first terminal application 12a. The second terminal application first input command 18d is also referred to as the first input command 18d of the second terminal application 12b.

[0094] When the patient 8 thinks of the thought 9, the module 10 (e.g., via the processor) may associate the neural-related signals 17 associated with the thought 9 and / or features extracted therefrom with the input commands 18 to which the thought 9 is assigned, and the input commands 18 associated with the thought 9 may be sent by the module 10 (e.g., via the processor, controller, or transceiver) to their corresponding terminal applications 12. For example, if the thought 9 is assigned to the first input command 18a of the first terminal application 12a, then when the patient 8 thinks of the thought 9, the first input command 18a of the first terminal application 12a may be sent to the first terminal application 12a, and if the thought 9 is assigned to the first input command 18d of the second terminal application 12b, then when the patient 8 thinks of the thought 9, the first input command 18d of the second terminal application 12b may be sent to the second terminal application 12b. Thus, a single thought (e.g., thought 9) may be interfaced with or used to control multiple terminal applications 12 (the first terminal application 12a and the second terminal application 12b). Any number of thoughts 9 may be used as switches. The number of ideas 9 used as switches can correspond to, for example, the number of controls (e.g., input commands 18) required or desired to control the terminal application 12. Ideas 9 can be assigned to multiple terminal applications 12. For example, the neural-related signal 17 associated with the first idea and / or the features extracted therefrom can be assigned to the first terminal application first input command 18a, and can be assigned to the second terminal application first input command 18d. As another example, the neural-related signal 17 associated with the second idea and / or the features extracted therefrom can be assigned to the first terminal application second input command 18b, and can be assigned to the third terminal application first input command. The first idea can be different from the second idea. Multiple terminal applications 12 (e.g., the first terminal application 12a and the second terminal application 12b) can operate independently of each other. In the case where the module 10 is used to control a single terminal application (e.g., the first terminal application 12a), the first idea can be assigned to multiple input commands 18. For example, the first idea alone can activate the first input command, and the first idea together with the second idea can activate the second input command different from the first input command. The idea 9 can thus act as a universal switch even in the case where only a single terminal application 12 is controlled by the module 10, because a single idea can be combined with other ideas to form an additional switch. As another example, a single idea can be combined with other ideas to form an additional universal switch that can be assigned to any input command 18, where multiple terminal applications 12 are controllable by the module 10 via the idea 9.

[0095] Figure 2A-2D It is shown that the neural interface 14 may be a stent 101. The stent 101 may have struts 108 and sensors 131 (eg, electrodes). The stent 101 may be collapsible and expandable.

[0096] Figure 2A-2D It is further shown that the stent 101 can be implanted in a blood vessel of the human brain, for example, a blood vessel passing through the human superior sagittal sinus. Figure 2A An exemplary module 10 is shown, and Figure 2B-Figure 2D Shows Figure 2A Three enlarged views of the module 10. The support 101 can be implanted, for example, via the jugular vein in the superior sagittal sinus (SSS) overlying the primary motor cortex to passively record brain signals and / or stimulate tissue. The support 101 can detect, for example, neural-related signals 17 associated with thoughts 9 via the sensor 131, so that people paralyzed due to neurological damage or disease can communicate, improve mobility and potentially achieve independence through direct brain control of assistive technologies (such as terminal applications 12). Figure 2C It is shown that the communication conduit 24 (eg, stent lead) can extend from the stent 101, through the jugular vein wall, and tunnel under the skin to the subclavian pouch. In this way, the communication conduit 24 can facilitate communication between the stent 101 and the telemetry unit 22.

[0097] Figure 2A-2D It is further shown that the terminal application 12 may be a wheelchair.

[0098] Figure 3 It is shown that the neural interface 14 (eg, the support 101 ) can be a wireless sensor system 30 that can communicate wirelessly with the host device 16 (eg, without the telemetry unit 22 ). Figure 3 A stent 101 is shown within a blood vessel 104 covering the motor cortex of a patient 8, which picks up the nerve-related signals and relays the information to a wireless transmitter 32 located on the stent 101. The nerve-related signals recorded by the stent 101 can be wirelessly transmitted through the patient's skull to a wireless transceiver 34 (e.g., placed on the head), which in turn decodes the acquired nerve-related signals and transmits them to the host device 16. As another example, the wireless transceiver 34 can be part of the host device 16.

[0099] Figure 3 It is further shown that the end application 12 may be a prosthetic arm.

[0100] Figure 4 It is shown that a neural interface 14 (e.g., a stent 101) can be used to record neural-related signals 17 from the brain, such as from neurons in the superior sagittal sinus (SSS) or branch cortical veins, including the following steps: (A) implanting the neural interface 14 into a blood vessel 104 in the brain (e.g., the superior sagittal sinus, a branch cortical vein); (b) recording neural-related signals; (c) generating data representing the recorded neural-related signals; and (d) transmitting the data to a host device 16 (e.g., with or without a telemetry unit 22).

[0101] All of the contents of U.S. Patent Application No. 16 / 054,657, filed on August 3, 2018, are incorporated herein by reference in their entirety for all purposes, including all systems, devices, and methods disclosed therein, and including any combination of features and operations disclosed therein. For example, the neural interface 14 (e.g., the support 101) can be, for example, any support (e.g., the support 101) disclosed in U.S. Patent Application No. 16 / 054,657, filed on August 3, 2018.

[0102] Using module 10, patient 8 can be prepared to interface with multiple terminal applications 12. Using module 10, patient 8 can use one type of electronic command to perform multiple tasks, which electronic command is based on a specific task-independent thought (e.g., thought 9). For example, using module 10, patient 8 can perform multiple tasks with a single task-independent thought (e.g., thought 9).

[0103] For example, Figure 5 A variation of a method 50 of preparing an individual to interface with an electronic device or software (eg, with terminal application 12 ) is shown having operations 52 , 54 , 56 , and 58 . Figure 5 It is shown that method 50 may include: in operation 52, when the individual generates a first task-irrelevant thought, measuring a neural-related signal of the individual to obtain a first sensed neural signal. Method 50 may include transmitting the first sensed neural signal to a processing unit in operation 54. Method 50 may include associating the first task-irrelevant thought and the first sensed neural signal with a first input command in operation 56. Method 50 may include compiling the first task-irrelevant thought, the first sensed neural signal, and the first input command into an electronic database in operation 58.

[0104] As another example, Figure 6 A variation of a method 60 of controlling a first device and a second device (eg, a first terminal application 12a and a second terminal application 12b) is shown having operations 62, 64, 66, and 68. Figure 6 It is shown that method 60 may include: in operation 62, when the individual generates a task-irrelevant thought, measuring a neural-related signal of the individual to obtain a sensed neural signal. Method 60 may include transmitting the sensed neural signal to a processor in operation 64. The method may include associating the sensed neural signal with a first device input command and a second device input command via the processor in operation 66. The method may include: in operation 68, when associating the sensed neural signal with the first device input command and the second device input command, electrically transmitting the first device input command to the first device or electrically transmitting the second device input command to the second device.

[0105] As another example, Figure 7A variation of a method 70 of preparing an individual to interface with a first device and a second device (eg, a first terminal application 12a and a second terminal application 12b) is shown having operations 72, 74, 76, 78, and 80. Figure 7 It is shown that method 70 may include: in operation 72, when the individual generates a task-specific thought by thinking of the first task, measuring the brain-related signal of the individual to obtain a sensed brain-related signal. The method may include transmitting the sensed brain-related signal to the processing unit in operation 74. The method may include associating the sensed brain-related signal with a first device input command associated with the first device task via the processing unit in operation 76. The first device task may be different from the first task. The method may include: in operation 78, associating the sensed brain-related signal with a second device input command associated with the second device task via the processing unit. The second device task may be different from the first device task and the first task. The method may include: in operation 80, when associating the sensed brain-related signal with the first device input command and the second device input command, the first device input command is electrically transmitted to the first device to perform the first device task associated with the first device input command, or the second device input command is electrically transmitted to the second device to perform the second device task associated with the second device input command.

[0106] As another example, Figure 5-Figure 7 A variation of the method of controlling multiple terminal applications 12 with a common switch (eg, idea 9) is shown.

[0107] As another example, Figure 5-Figure 7 The operations illustrated may be performed and repeated in any order and in any combination. Figure 5-Figure 7 The present disclosure is not limited in any way to the methods shown or the specific order of operations listed. For example, the operations listed in methods 50, 60 and 70 can be performed in any order, or one or more operations can be omitted or added.

[0108] As another example, a variation of the method using module 10 may include measuring a brain-related signal of an individual to obtain a first sensed brain-related signal when the individual generates a task-irrelevant thought (e.g., thought 9). The method may include transmitting the first sensed brain-related signal to a processing unit. The method may include the processing unit applying a mathematical algorithm or model to detect a brain-related signal corresponding to when the individual generates thought 9. The method may include associating the task-irrelevant thought and the first sensed brain-related signal with one or more input commands 18 in number N. The method may include compiling the task-irrelevant thought (e.g., thought 9), the first sensed brain-related signal, and the N input commands 18 into an electronic database. The method may include monitoring the first sensed brain-related signal of the individual (e.g., using a neural interface), and when the first sensed brain-related signal is detected, electrically transmitting at least one of the N input commands 18 to a control system. The control system may be a control system of a terminal application 12. The N input commands 18 may be, for example, 1 to 100 input commands 18, including every 1 input command 18 in the range. N input commands may be assigned to Y terminal applications 12, where the Y terminal applications may be, for example, 1 to 100 terminal applications 12, including every 1 increment of terminal applications 12 within the range. As another example, the Y terminal applications 12 may be, for example, 2 to 100 terminal applications 12, including every 1 increment of terminal applications 12 within the range. The Y terminal applications 12 may include, for example, at least one of controlling a mouse cursor, controlling a wheelchair, and controlling a speller. The N input commands 18 may be at least one of a binary input associated with a task-irrelevant thought, a hierarchical input associated with a task-irrelevant thought, and a continuous trajectory input associated with a task-irrelevant thought. The method may include associating M detections of a first sensory brain-related signal with the N input commands 18, where M is 1 to 10 or fewer detections. For example, when M is one detection, a task-irrelevant thought (e.g., thought 9) and a first sensory brain-related signal may be associated with a first input command (e.g., first input command 18a). As another example, when M is two detections, the task-independent thought (e.g., thought 9) and the first sensory brain-related signal can be associated with the second input command (e.g., the second input command 18b). As yet another example, when M is three detections, the task-independent thought (e.g., thought 9) and the first sensory brain-related signal can be associated with the third input command (e.g., the third input command 18c). The first, second, and third input commands can be associated with one or more terminal applications 12. For example, the first input command can be an input command for a first terminal application, the second input command can be an input command for a second terminal application, and the third input command can be an input command for a third application, so that a single thought 9 can control multiple terminal applications 12.Each number of the M detections of idea 9 can be assigned to multiple terminal applications, so that the terminal number of M detections (e.g., 1, 2, or 3 detections) can act as a universal switch that can be assigned to any input command 18. The first, second, and third input commands can be associated with different functions. The first, second, and third input commands can be associated with the same function, so that the first input command is associated with the function first parameter, the second input command is associated with the function second parameter, and the third input command is associated with the function third parameter. The first, second, and third parameters of the function can be, for example, progressive levels of speed, volume, or both. For example, the progressive level of speed can be associated with the movement of a wheelchair, with the movement of a mouse cursor on a screen, or both. The progressive level of volume can be associated, for example, with the sound volume of a sound system of a car, a computer, a phone, or any combination thereof. At least one of the N input commands 18 can be a click and hold command associated with a computer mouse. The method can include associating a combination of task-independent ideas (e.g., idea 9) with the N input commands 18. The method may include associating a combination of Z task-irrelevant thoughts with N input commands 18, wherein the Z task-irrelevant thoughts may be 2 to 10 or more task-irrelevant thoughts, or more broadly, 1 to 1000 or more task-irrelevant thoughts, including every 1 unit increment within these ranges. At least one of the Z task-irrelevant thoughts may be a task-irrelevant thought, wherein the task-irrelevant thought may be a first task-irrelevant thought, such that the method may include measuring a brain-related signal of the individual to obtain a second sensed brain-related signal when the individual generates a second task-irrelevant thought, transmitting the second sensed brain-related signal to a processing unit, associating the second task-irrelevant thought and the second sensed brain-related signal with N2 input commands, wherein when a combination of the first and second sensed brain-related signals is obtained sequentially or simultaneously, the combination may be associated with N3 input commands. The task-irrelevant thought may be a thought to move a limb. The first sensed brain-related signal may be at least one of an electrical activity of brain tissue and a functional activity of brain tissue. Any of the operations in this exemplary method may be performed in any combination and in any order.

[0109] As another example, a variation of the method using module 10 may include measuring a brain-related signal of an individual to obtain a first sensed brain-related signal when the individual generates a first task-specific thought by thinking of a first task (e.g., by thinking of thought 9). The method may include transmitting the first sensed brain-related signal to a processing unit. The method may include the processing unit applying a mathematical algorithm or model to detect a brain-related signal corresponding to when the individual generates a thought. The method may include associating the first sensed brain-related signal with a first task-specific input command (e.g., input command 18) associated with a second task, wherein the second task is different from the first task (e.g., so that thought 9 involves a task different from the task that input command 18 is configured to perform). The first task-specific thought may be independent of the associating step. The method may include assigning the second task to the first task-specific command instruction without regard to the first task. The method may include reassigning the third task to the first task-specific command instruction without regard to the first task and the second task. The method may include compiling the first task-specific thought, the first sensed brain-related signal, and the first task-specific input command into an electronic database. The method may include monitoring the first sensed brain-related signal of the individual, and upon detecting the first sensed brain-related signal, electrically transmitting the first task-specific input command to the control system. The first task-specific idea may be, for example, about a physical task, a non-physical task, or both. The generated idea may be, for example, a single idea or a composite idea. The composite idea may be two or more non-simultaneous ideas, two or more simultaneous ideas, and / or a series of two or more simultaneous ideas. Any of the operations in the exemplary method may be performed in any combination and in any order.

[0110] As another example, a variation of the method using module 10 may include measuring a brain-related signal of an individual to obtain a first sensed brain-related signal when the individual thinks a first thought. The method may include transmitting the first sensed brain-related signal to a processing unit. The method may include the processing unit applying a mathematical algorithm or model to detect a brain-related signal corresponding to when the individual generates a thought. The method may include generating a first command signal based on the first sensed brain-related signal. The method may include assigning a first task to the first command signal without regard to the first thought. The method may include separating the first thought from the first sensed brain electrical activity. The method may include reassigning a second task to the first command signal without regard to the first thought and the first task. The method may include compiling the first thought, the first sensed brain-related signal, and the first command signal into an electronic database. The method may include monitoring the first sensed brain-related signal of the individual, and upon detecting the first sensed brain-related signal, electrically transmitting a first input command to a control system. The first thought may include, for example, a thought about a real or imagined muscle contraction, a real or imagined memory, or both, or any abstract thought. The first thought may be, for example, a single thought or a composite thought. Any of the operations in this exemplary method may be performed in any combination and in any order.

[0111] As another example, a variation of the method using module 10 may include measuring the electrical activity of the brain tissue of the individual to obtain a first sensed brain electrical activity when the individual thinks about the first idea. The method may include transmitting the first sensed brain electrical activity to a processing unit. The method may include the processing unit applying a mathematical algorithm or model to detect a brain-related signal corresponding to when the individual generates an idea. The method may include generating a first command signal based on the first sensed brain electrical activity. The method may include assigning a first task and a second task to the first command signal. The first task may be associated with a first device, and wherein the second task is associated with a second device. The first task may be associated with a first application of the first device, and wherein the second task is associated with a second application of the first device. The method may include assigning the first task to the first command signal without considering the first idea. The method may include assigning the second task to the first command signal without considering the first idea. The method may include compiling the first idea, the first sensed brain electrical activity, and the first command signal into an electronic database. The method may include monitoring the first sensed brain electrical activity of the individual, and upon detecting the first sensed brain electrical activity, electrically transmitting the first command signal to a control system. Any of the operations in this exemplary method may be performed in any combination and in any order.

[0112] As another example, a variation of the method using module 10 may include measuring a neural-related signal of an individual to obtain a first sensed neural signal when the individual generates a task-irrelevant thought. The method may include transmitting the first sensed neural signal to a processing unit. The method may include the processing unit applying a mathematical algorithm or model to detect a brain-related signal corresponding to when the individual generates a task-irrelevant thought. The method may include associating the task-irrelevant thought and the first sensed neural signal with a first input command. The method may include compiling the task-irrelevant thought, the first sensed neural signal, and the first input command into an electronic database. The method may include monitoring the first sensed neural signal of the individual, and when the first sensed neural signal is detected, electrically transmitting the first input command to a control system. The neural-related signal may be a brain-related signal. The neural-related signal may be measured from neural tissue in the brain of the individual. Any of the operations in this exemplary method may be performed in any combination and in any order.

[0113] As another example, a variation of the method using module 10 may include measuring a neural-related signal of an individual to obtain a first sensed neural-related signal when the individual generates a first task-specific thought by thinking of a first task. The method may include transmitting the first sensed neural-related signal to a processing unit. The method may include the processing unit applying a mathematical algorithm or model to detect a brain-related signal corresponding to when the individual generates a thought. The method may include associating the first sensed neural-related signal with a first task-specific input command associated with a second task, wherein the second task is different from the first task, thereby providing a mechanism for the user to control multiple tasks with different task-specific inputs using a single user-generated thought. The method may include compiling task-independent thoughts, first sensed neural signals, first input commands, and corresponding tasks into an electronic database. The method may include utilizing a memory of an electronic database to automatically group task-independent thoughts, sensed brain-related signals, and combinations of one or more inputs of a number N based on tasks, brain-related signals, or thoughts to automatically map control functions for automatic system settings for use. The neural-related signal may be a neural-related signal of brain tissue. Any of the operations in this exemplary method may be performed in any combination and in any order.

[0114] Module 10 may perform any combination of any of the methods, and may perform any operations of any of the methods disclosed herein.

[0115] The claims are not limited to the exemplary variations shown in the drawings, but may claim any features disclosed or envisioned as a whole in the present disclosure. Any element described herein as a singular may be plural (i.e., any element described as "one" may be more than one). Any element of a genus element may have the features or elements of any other element of the genus. For reasons of clarity, some elements may not be present in each figure. The above-mentioned configurations, elements or complete assemblies and methods for implementing the present disclosure and their elements, as well as variations of various aspects of the present disclosure may be combined and modified with each other in any combination, and each combination is thus explicitly disclosed. All devices, apparatuses, systems and methods described herein may be used for medical (e.g., diagnosis, treatment or rehabilitation) or non-medical purposes. The words "may" and "can" are interchangeable (e.g., "may" can be replaced by "can", and "can" can be replaced by "can"). Any range disclosed may include any sub-range of the disclosed range, for example, a range of 1-10 units may include 2-10 units, 8-10 units or any other sub-range. Any phrase involving an "A and / or B" structure may mean (1) A alone, (2) B alone, (3) A and B together, or any combination of (1), (2), and (3), such as (1) and (2), (1) and (3), (2) and (3), and (1), (2), and (3). For example, the sentence "the module 10 (e.g., the host device 16) can communicate with one or more terminal applications 12 by wire and / or wirelessly" in the present disclosure may include (1) the module 10 (e.g., the host device 16) can communicate with one or more terminal applications 12 by wire, (2) the module 10 (e.g., the host device 16) can communicate with one or more terminal applications 12 by wireless, (3) the module 10 (e.g., the host device 16) can communicate with one or more terminal applications 12 by wire and wirelessly, or any combination of (1), (2), and (3).

Claims

1. A method for preparing an individual to interface with an electronic device or software, the method comprising: When the individual generates a first task-irrelevant thought, measuring a neural-related signal of the individual to obtain a first sensed neural signal; transmitting the first sensed neural signal to a processing unit; associating the first task-irrelevant thought and the first sensed neural signal with a first input command; and The first task-irrelevant thought, the first sensed neural signal, and the first input command are compiled into an electronic database.

2. The method according to claim 1, wherein: The first input command is an input command of a first terminal application.

3. The method of claim 2, further comprising associating the first task-irrelevant thought and the first sensed neural signal with a second input command.

4. The method according to claim 3, wherein: The second input command is an input command of a second terminal application. 5 . The method of claim 4 , further comprising controlling the first terminal application with the first input command when the first sensed neural signal is detected. 6 . The method according to claim 5 , further comprising controlling the second terminal application with the second input command when the first sensed neural signal is detected.

7. The method of claim 4, further comprising compiling the first task-irrelevant thought, the first sensed neural signal, and the second input command into the electronic database.

8. The method according to claim 4, wherein: The first sensed neural signal is a first sensed brain electrical activity.

9. The method according to claim 4, wherein: Measuring the nerve-related signal of the individual includes measuring the nerve-related signal of the individual using an implantable intravascular device.

10. The method of claim 4, further comprising monitoring the individual for the first sensed neural signal, and upon detection of the first sensed neural signal, electronically transmitting the first input command to the first terminal application or to the second terminal application.

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