Nerve monitoring system

Abstract

A brain-computer interface ('BCI') system provides more meaningful autonomy and independence for paralyzed individuals. Comprising a BCI system used by an individual that requires less assistance by a caregiver or even does not require a caregiver, providing an objective and functional measurement of the effectiveness of a motor nerve prosthesis in restoring motor output.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. Provisional Application No. 63 / 367,592, filed on July 1, 2022, U.S. Provisional Application No. 63 / 502,831, filed on May 17, 2023, and U.S. Provisional Application No. 63 / 506,152, filed on June 5, 2023, the entire contents of each of which are incorporated herein by reference. Background Art

[0003] It is now understood that, in most cases, the human brain functions as a well-coordinated network composed of a collection of diverse brain regions, each of which is an independent network of brain tissue and cells responsible for a specific purpose. Statistical analysis of functional magnetic resonance imaging (fMRI) now allows neuroscientists to map the brain regions responsible for specific tasks. Furthermore, it is understood that many cognitive tasks are performed through networks of discrete, "functionally connected" brain regions. Therefore, the brain can be considered a distributed neural network that coordinates a series of subnetworks associated with various brain regions, each of which is associated with a specific purpose.

[0004] Currently, conventional methods exist for attempting to access these brain regions. Such generally known methods include deep brain stimulation ("DBS"), which involves implanting electrodes within a specific region of the brain to generate electrical impulses in that region in an attempt to stimulate or modulate brain activity for therapeutic or other purposes, and electrocorticography ("ECoG"), which enables neuromonitoring of brain regions for diagnostic purposes.

[0005] DBS involves a surgical procedure in which small holes are made in the skull to implant electrodes and a controller or pacemaker-like device electrically connected to the electrodes to control the stimulation. Typically, the device is placed under the skin on the chest. The amount of stimulation in deep brain stimulation can be controlled by a controller or pacemaker-like device, with wires / leads connecting the controller device to the electrodes located in the brain.

[0006] DBS can be used to treat a variety of neurological conditions, including tremor, Parkinson's disease, dystonia, epilepsy, Tourette syndrome, chronic pain, and obsessive-compulsive disorder. Furthermore, deep brain stimulation has the potential to treat major depression, stroke rehabilitation, addiction, and dementia.

[0007] ECoG can provide a method for recording high-fidelity brain activity, for example, during surgery (intraoperative neuromonitoring), where real-time recordings of brain activity enable treating surgeons to make immediate decisions, improving treatment safety. Long-term recordings are used for seizure detection and to aid mapping to improve the safety of tumor resection by limiting resection of healthy brain. However, ECoG requires placement of electrode arrays directly on the brain surface after the brain is exposed through a craniotomy, for example, using subdural or epidural arrays. Consequently, their applications are extremely limited.

[0008] Figure 1 A conventional method of accessing a brain region is shown using a brain stimulation device 20 comprising electrodes 22 implanted within the brain 12 of an individual 10. As shown, implantation requires surgical puncture of the skull 14 with the device 20 directed toward the region of interest 30. Additionally, leads 16 couple the device 20 to a controller / transceiver / generator 18.

[0009] In conventional DBS surgery, the ordinary surgical procedure required to surgically implant the device 20 carries numerous risks. Furthermore, in DBS surgery, the surgical procedure itself carries risks, as conventional procedures require approximate or non-invasive attempts to locate the region of interest 30. The surgeon must then attempt to physically position the electrodes 22 of the device 20 in or near the region of interest 30 so that the desired effect can be achieved. In some cases, positioning the electrodes 20 may be a trial-and-error process, requiring multiple surgical attempts and multiple surgical insertion sites. Regardless of the number of attempts, the act of inserting the device 20 to position the electrodes 22 in the region of interest 30 causes collateral damage to brain tissue located in the path between the region of interest and the insertion point in the skull.

[0010] Currently, this surgical procedure carries surgical risks including: cerebral hemorrhage, stroke, infection, collateral damage to brain tissue, collateral damage to vascular structures within the brain, temporary pain, and inflammation at the surgical site. In addition to surgical risks, DBS also carries the risk of side effects if the electrodes stimulate or affect areas outside of the region of interest 30. These risks may include: breathing problems, nausea, heart problems, seizures, headaches, confusion, etc. However, because the device and the tissue surrounding the implant site heal, attempting to remove the DBS device after a period of time introduces additional risks.

[0011] However, conventional methods designed to access the brain's many subnetworks suffer from deficiencies that prevent them from maximizing the benefits of accessing and directly communicating / stimulating these subnetworks.

[0012] Conventional invasive methods involving direct brain puncture result in persistent scarring due to gliosis. Due to the invasive nature of the craniotomy and the progressive nature of scar accumulation due to gliosis, removal and replacement of conventional DBS electrodes in the brain is not feasible.

[0013] In addition to the issues discussed above, the development of brain-computer interface ("BCI") technology is currently focused on safety and enabling paralyzed individuals to use BCI systems to control electronic devices, including prosthetic arms and computers, to complete a variety of daily tasks. Restoration of continuous and independent motor output is necessary to allow people with complete or partial paralysis to perform computer control. BCI systems are expected to restore lost neurological function, including motor neuroprostheses (MNPs) to restore an individual's motor ability. Implantable MNPs can directly infer motor intent by detecting local brain signals and transmitting motor control signals outside the brain to generate motor output and subsequently control computer actions or other electronic devices. In one variation, this physiological function can be performed by motor neurons in the individual.

[0014] However, while conventional BCI systems provide paralyzed individuals with a degree of autonomy through control of the device, currently available BCI systems provide only very limited overall autonomy to paralyzed individuals. For example, paralyzed individuals using BCI systems typically require assistance with: setting up or turning on the BCI system (including charging / recharging); calibrating the system for individual use, including learning how the individual must think in order to generate useful electronic commands; and configuring the individual (adjusting the individual's screen, antenna, and / or posture, etc., to allow them to use the system, rather than configuring the system itself).

[0015] There is a need for BCI systems that provide paralyzed individuals with more meaningful autonomy and independence. This meaningful autonomy and independence can be provided by a BCI system used by the individual with less or no assistance from a caregiver. There is also a need for objective and functional measurements of the effectiveness of MNPs in restoring motor output. One approach relies on the concept of digitized motor output (DMO), which is the motor output directly decoded from neural recordings when an individual attempts a limb movement, and the BCIU converts this neural intent into commands to control electronic devices. DMOs can be divided into discrete and continuous motor control representations, with different degrees of freedom.

[0016] The need for at least intermittent independence can also benefit patients when caregivers do not understand their needs or when they communicate their dissatisfaction or fears about their caregivers to a third party. Summary of the Invention

[0017] The ability to access the brain's functional distributed networks allows for direct access, monitoring, and / or communication with specific areas of the brain, potentially enabling technological improvements in a variety of areas, including, but not limited to, healthcare, quality of life, improved use of technology by individuals, and improved communication capabilities within groups of individuals' networks. For example, direct access to such neural distributed networks allows for improvements in an individual's routine healthcare routine and / or improved control of machinery by an individual. In further variations, the ability to directly access, monitor, and / or communicate with an individual's neural distributed networks allows for improved communication with that individual and / or between individuals whose respective neural distributed networks are configured to be directly networked.

[0018] The present disclosure includes one or more methods for adjusting a neural interface by monitoring neural activity of an individual, wherein the neural interface includes a neural monitoring device operably connected to a control unit, wherein the control unit is configured to generate an output control signal for interacting with an external electronic device, the method comprising: providing a signal from the neural monitoring device implanted in the individual to the control unit, wherein the signal represents neural activity of the individual, and wherein detection of predetermined neural activity causes the control unit to generate the output control signal; determining an activity level of the individual by monitoring the neural activity of the individual; and wherein the control unit is configured to adjust the neural interface from a first operating configuration to a second operating configuration upon determining that the activity level satisfies a first predetermined condition, wherein power consumption of the neural interface in the first operating configuration is different from power consumption of the neural interface in the second operating configuration.

[0019] A variation of the method includes a first predetermined condition comprising a sleep state of the individual, and wherein determining the activity level comprises determining the sleep state of the individual by evaluating neural activity against a neural sleep indicator. The first predetermined condition may comprise a failure to generate an output control signal within a predefined time period.

[0020] In further variations, the control unit may be further configured to adjust the neural interface from the first operating configuration to the second operating configuration when the output control signal is associated with an idle command instruction.

[0021] The neural interface can be configured to provide perceptible feedback to the individual indicating whether the neural interface is in the first operating configuration or the second operating configuration. The neural interface can be configured to allow the individual to maintain the neural interface in the first operating configuration. Variations of the control unit can be further configured to transmit an idle signal to the external electronic device upon or before adjusting to the second operating configuration.

[0022] Another variation of the method includes determining an activity level of the individual by monitoring the individual's neural activity while the neural interface is in a second operating configuration, and wherein the control unit is further configured to adjust the neural interface from the second operating configuration to the first operating configuration upon determining that the activity level satisfies a second predetermined condition.

[0023] The control unit may be further configured to adjust the neural interface from the second operating configuration to the first operating configuration when the output control signal is associated with the active command instruction. The control unit may be further configured to adjust the neural interface from the second operating configuration to the first operating configuration when the individual generates at least one output control signal.

[0024] Another variation of the methods described herein includes a method of varying a communication frequency in a neural interface by monitoring neural activity of an individual, wherein the neural interface includes a neural monitoring device operably configured to communicate with a control unit at a communication rate, and wherein the control unit is configured to generate output control signals for interacting with an external electronic device.

[0025] An example of such a method includes providing a signal from a neural monitoring device implanted in an individual to a control unit, wherein the signal represents neural activity of the individual, and wherein detection of predetermined neural activity causes the control unit to generate an output control signal; determining an activity level of the individual by monitoring the neural activity of the individual; and wherein the control unit is configured to change the neural interface from a first operating configuration to a second operating configuration upon determining that the activity level satisfies a first predetermined condition, wherein a communication rate in the first operating configuration is different from a communication rate in the second operating configuration.

[0026] Another example of a method according to the present disclosure includes: a method for improving the autonomy of a paralyzed individual in operating an external electronic device by providing a brain-computer interface, the brain-computer interface being configured to monitor the neural activity of the paralyzed individual, wherein the brain-computer interface includes a neural monitoring device operably connected to a control unit, wherein the control unit is configured to generate an output signal for interacting with the external electronic device; wherein the brain-computer interface is configured to enter an idle mode, the brain-computer interface consuming less power in the idle mode than in the active mode; and receiving an activation signal from the paralyzed individual to switch the brain-computer interface from the idle mode to the active mode without the assistance of a caregiver.

[0027] In the method, coupling the control unit and the external electronic device may include reducing calibration time of the brain-computer interface when entering the active mode. The control unit and the external electronic device may be coupled wirelessly.

[0028] Variations of the method include a brain-computer interface configured to connect to a rechargeable power source for a paralyzed individual, or configured to transmit operational data from the brain-computer interface to a remote electronic dashboard, wherein the remote electronic dashboard allows the individual to monitor the activity of the brain-computer interface. The brain-computer interface can be configured to wirelessly transmit operational data from the brain-computer interface to the remote electronic dashboard. The brain-computer interface can be configured to have a latency of five seconds or less (however, any longer duration is within the scope of the present disclosure).

[0029] Another method for improving the autonomy of a paralyzed individual in operating an external electronic device may include: providing a brain-computer interface configured to monitor the neural activity of the paralyzed individual, wherein the brain-computer interface includes a neural monitoring device operably connected to a control unit, wherein the control unit is configured to generate an output control signal for interacting with the external electronic device in response to the neural activity of the paralyzed individual associated with a prompt signal generated by the brain-computer interface; and calibrating the brain-computer interface within a minimum time period, wherein calibrating the brain-computer interface allows the paralyzed individual to activate the output control signal after the paralyzed individual has not used the brain-computer interface for a period of time.

[0030] Yet another variation of a method for increasing the autonomy of a paralyzed individual in operating an external electronic device may include providing a brain-computer interface configured to monitor neural activity of the paralyzed individual, wherein the brain-computer interface includes a neural monitoring device operably connected to a control unit, wherein the control unit is configured to generate an output control signal for interacting with the external electronic device when the paralyzed individual generates neural activity in response to a prompt generated by the brain-computer interface, wherein the brain-computer interface includes a high-precision interface ratio, wherein the high-precision interface ratio is a measure between intentional neural activity associated with the prompt and neural activity not associated with the prompt. The high-precision interface ratio includes 95%.

[0031] The present disclosure also includes a brain-computer interface for increasing the autonomy of a paralyzed individual in operating an external electronic device. An example of such a brain-computer interface may include: a neural monitoring device configured to detect neural activity of the paralyzed individual; a control unit operably connected to the neural monitoring device, wherein the control unit is configured to generate a prompt on a display, wherein the prompt is associated with one or more commands, wherein when the paralyzed individual generates neural activity associated with an intention to select the prompt, the control unit generates an output control signal for interacting with the external electronic device; and wherein the control unit is configured to generate the prompt and the output control signal within a minimum time.

[0032] Another example of a brain-computer interface system for increasing the autonomy of an individual in interacting with an electronic device, wherein the individual is fully or partially paralyzed, the brain-computer interface system comprising: a neural monitoring device, the neural monitoring device being coupled to the individual and configured to detect neural activity from the individual; a control unit, the control unit being operably coupled to the neural monitoring device and removably coupled to the individual, wherein the control unit is configured to interact with the electronic device when the individual generates neural activity; and wherein the neural monitoring device is further configured to electronically communicate with an electronic network such that when the control unit is disconnected from the individual, the individual is still able to communicate with the electronic network using neural activity. Examples of neural monitoring devices include an implant and an internal unit, wherein the implant is configured to be positioned near or in neural tissue, and the internal unit is in electrical communication with the implant. Optionally, the device can be an external device, a percutaneously positioned device, a transvascularly positioned device, or a combination of any of the foregoing.

[0033] In one variation, the brain-computer interface system includes a neuromonitoring device configured to electronically communicate with the electronic network independently of the control unit. Alternatively or in combination, the neuromonitoring device is configured to electronically communicate with the electronic network using the control unit.

[0034] Another variation of a brain-computer interface system for increasing the autonomy of an individual in interacting with an electronic device, wherein the individual is fully or partially paralyzed, the brain-computer interface system comprising: a neural monitoring device coupled to the individual and configured to detect neural activity from the individual; a control unit operably coupled to the neural monitoring device and removably coupled to the individual, wherein the control unit is configured to interact with the electronic device when the individual generates neural activity; and wherein the control unit is further configured to electronically communicate with an electronic network such that when the electronic device is disconnected from the individual, the individual is still able to communicate with the electronic network using the neural activity.

[0035] The present disclosure also includes a method for enhancing the autonomy of an individual using a brain-computer interface, wherein the individual is fully or partially paralyzed, the method comprising: positioning a neural monitoring device in or on the individual, the neural monitoring device being configured to detect neural activity from the individual; disconnecting a control unit from the individual, wherein the control unit is configured to be operably coupled to the neural monitoring device and configured to interact with one or more electronic devices when the individual generates neural activity; and connecting the neural monitoring device to an electronic network so that the individual maintains the ability to communicate with the electronic network using the neural activity.

[0036] The method may further include coupling the nerve monitoring device to the electronic network by coupling the nerve monitoring device to the electronic network using the control unit when the control unit is detached from the one or more electronic devices.

[0037] In another variation, the method may include coupling the nerve monitoring device to the electronic network by coupling the nerve monitoring device to the electronic network without using the control unit.Another variation includes coupling the nerve monitoring device to the electronic network but includes decoupling the control unit from the individual.

[0038] In any of the above methods, the nerve monitoring device may include an implant and an internal unit, wherein the implant is configured to be positioned near or in neural tissue, and the internal unit is in electrical communication with the implant. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A conventional method of accessing a brain region using a brain stimulation device comprising electrodes implanted within an individual's brain is shown.

[0040] Figure 2A A diagram showing the cerebral cortex of the brain with a vasculature network supplying various regions of the cerebral cortex of the brain.

[0041] Figure 2B is a schematic diagram of the brain omitting the vasculature in the various cytoarchitectonic regions of the cerebral cortex.

[0042] Figure 3 A variation of an intravascular electrode array as part of a microwire monitoring / stimulation probe is shown.

[0043] Figure 4A A first variation of a system for directly accessing and monitoring specific areas or sub-networks of the brain via vascular access is shown.

[0044] Figure 4B Variations of systems for directly accessing and monitoring discrete regions or subnetworks of the brain via vascular access are shown.

[0045] Figure 5 Variations of systems are shown that include multiple microwire monitoring probes coupled to one or more monitoring devices.

[0046] Figure 6

[0014] An application of the system described herein is shown in which the brain's distributed neural networks are used to improve technology control, motor control, emotion monitoring, decision making monitoring, sensory feedback, auditory feedback, visual feedback, and communication with individuals.

[0047] Figure 7 An example of a system using a distributed neural network of individuals to improve data communication between individuals to improve interaction with any type of external device or machine is shown.

[0048] Figure 8Another variation of using a distributed neural network to improve data communication with individuals for monitoring individuals is shown.

[0049] Figure 9 A variation of creating a brain-to-brain network between at least two individuals using a distributed neural network is shown.

[0050] Figure 10 Shown is a demonstration of a brain-computer interface that provides enhanced autonomy to individuals suffering from complete or partial paralysis. DETAILED DESCRIPTION

[0051] The present methods and apparatus involve electrodes configured for direct access, monitoring, and / or communication with specific brain regions or subnetworks via vascular access, with the goal of using direct access to send data to and from various subnetworks of the brain and individual associated nerves. As described below, the use of data communicated directly to and from these neural subnetworks can improve numerous fields, including but not limited to medical applications, control of machines and electronic devices, real-time feedback on goal-directed activities, and communications and consumer products.

[0052] Figure 2A An illustration of the cerebral cortex of brain 12 is shown with a network of vasculature 40 that supplies various regions of the cerebral cortex of brain 12. The methods and devices described herein use the vasculature 40 to position one or more electrodes near specific regions of the brain. Variations of the methods may include using veins and / or arteries to position the devices. In some variations, the electrodes are located in veins to avoid inadvertently reducing or blocking blood flow to brain tissue. In addition, as described below, the devices may be positioned entirely within a blood vessel. However, variations may include using devices or structures that penetrate the walls of blood vessels.

[0053] Figure 2BA schematic diagram of the brain 12 omitting the vasculature in the various cytoarchitectonic regions of the cerebral cortex (C1 to C46). These regions correspond to Brodmann areas, which are based on the organization of neurons observed in the cerebral cortex that correspond to various cortical functions of the cerebral cortex. C1, C2, and C3 represent the primary somatosensory cortex in the postcentral gyrus; C4 is the primary motor cortex; C5 is the superior parietal lobule; C6 is the premotor and supplementary motor cortexes; C7 is the visuomotor cortex; C8 – includes the frontal visual areas; C9 – the dorsolateral prefrontal cortex; C10 – the anterior prefrontal cortex (the superior and most anterior parts of the middle frontal gyri); C11 – the orbitofrontal area (the orbital gyrus and gyrus rectus, plus part of the anterior part of the superior frontal gyrus); C17 – the primary visual cortex (V1); C18 – the secondary visual cortex (V2); C19 – the associated visual cortex (V3, V4, V5); C20 – the inferior temporal gyrus; C21 – the middle temporal gyrus; and C22 – parts of the superior temporal gyrus, including Wernicke's area. area); C37 – the fusiform gyrus; C38 – the temporal pole (the anteriormost parts of the superior and middle temporal gyri); C39 – the angular gyrus, considered by some to be part of Wernicke's area; C40 – the superior parietal sulcus, considered by some to be part of Wernicke's area; C41 and C42 – the auditory cortex; C44 and C45 – Broca's area, which includes the pars opercularis and pars triangularis of the inferior frontal gyrus; and C46 – the dorsolateral prefrontal cortex.

[0054] The devices, methods, and systems described herein may benefit from or be combined with the intravascular carriers and electrode arrays and systems / methods for using neural signals disclosed in the following patents: US10575783, issued on March 3, 2020, US10485968, issued on November 26, 2019, US10729530, issued on August 4, 2020, and US10729530, issued on December 24, 2019. The US patent is US10512555; the publication number published on November 28, 2019 is US20190358445, the publication number published on October 25, 2018 is US20180303595, the publication number published on November 12, 2020 is US20200352697, the publication number published on February 7, 2019 is US20190038438, and the publication number published on March 1, 2020 is U.S. Patent Application No. 17 / 093,196, filed on November 9, 2020, U.S. Patent Application No. 17 / 093,196, filed on November 9, 2020, U.S. Patent Application No. 17 / 093,196, filed on November 9, 2020, U.S. Patent Application No. 17 / 093,196, filed on November 2 ... Application; PCT Application Nos. PCT / US2020 / 060780 and PCT / US2020 / 059509, both filed on November 6, 2020; U.S. Provisional Application Nos. 63 / 003,480, filed on April 1, 2020, 63 / 057,379, filed on July 28, 2020, and 63 / 062,633, filed on August 7, 2020. The contents of each of the above-mentioned U.S. patents, U.S. publications, U.S. applications, PCT applications, and U.S. provisional applications are incorporated herein by reference in their entirety.

[0055] Figure 3Another variation of an intravascular electrode array as part of a microwire monitoring / stimulation probe 100 is shown. As shown, the probe 100 includes one or more distal electrodes 108 located on a helical or sinusoidal 106 portion of a microwire 102. As described below, the nonlinear distal portion 106 includes an atraumatic tip 104 that allows the electrode 108 and distal portion 106 to be temporarily secured within a cerebral vessel without causing damage to the vessel or the brain. The nonlinear shape 106 can be used to attach the lead to the vessel wall and to position the electrode 108 in contact with the vessel wall. The nonlinear distal portion 106 can include a nitinol material or a nitinol core that allows the device to assume a nonlinear shape when unconstrained or activated by an electrical current. Examples of microwires can be found in U.S. Patents 6,260,458, 6,428,489, 6,431,039, 6,440,088, 6,553,880, 6,579,246, and 6,766,720, the entire contents of which are incorporated herein by reference.

[0056] In other variations, the entire microwire 102 can include a shape memory alloy. In most variations, the device 100 is configured to be removable from a blood vessel, for example, by pulling on the proximal end of the microwire 102. Other variations of the device 100 include nonlinear shapes at the electrode region 106, which can range from a spiral shape to a simple bend or any shape that allows anchoring in the delicate blood vessels of the brain. Alternatively, a series of electrodes 108 can be positioned on any structure that provides anchoring but does not restrict blood flow within the vessel.

[0057] Typically, the length and diameter of the microfilament 102 are such that it can be pushed into the distal vasculature in the brain. For example, the diameter of the microfilament 102 can be in the range of 0.010 to 0.018 inches. However, the size of the microfilament should be selected to allow the electrode portion to enter the remote area of ​​the brain. Optionally, the proximal portion of the microfilament 102 can have a larger diameter than the middle and distal regions to allow for increased pushability of the wire 102. The proximal end 112 of the microfilament 102 is coupled to a connector base 110, which communicates with monitoring software or other electronic / computing device 120 using a wireless or wired connection.

[0058] In addition to being non-invasive, the variations of the monitoring probe 100 described herein are configured to be removable after a short period of use. Alternatively, variations of the monitoring probe can remain implanted for several months and / or years. In any case, the device 100 can have an anti-thrombotic coating (e.g., heparin) to inhibit blood clotting.

[0059] Figure 4AA first variation of a system for directly accessing and monitoring specific regions or subnetworks of the brain 12 via a vascular approach is shown. In this variation, a microwire monitoring probe device 100 is pushed through the vasculature into a blood vessel 40 within the brain 12. The variation shown is shown as being implanted for a surgical procedure to provide brain monitoring during the procedure. In this variation, the device 100 can be removed after the surgery, or can remain implanted during post-operative monitoring. Thus, the proximal portion of the microwire 102 extends through one or more incisions 8 within the individual 10 for connection to a controller 110 or another connector base. For illustrative purposes, Figure 4A The system shown includes a single device 100. In practice, any number of microwire monitoring probe devices may be used. Furthermore, the device 100 can be positioned using a microcatheter (not shown) that constrains the electrode portion 106 prior to deployment. Alternatively, a caregiver can simply push the device 100 in a linear configuration. Once positioned within the desired area, the caregiver can apply an electrical current to the device to transition the electrode portion 106 from a linear configuration to a nonlinear configuration, allowing the device to remain anchored in the desired location.

[0060] As shown, the distal portion 106 of the device is configured to detect neural activity and remain temporarily anchored within a blood vessel. The device 100 is deployed within a blood vessel and adjacent to a region of interest 50. In this example, the region of interest 50 represents an area of ​​brain tissue that one wants to remove or inactivate. Such surgical procedures may involve tumor resection, brain tissue resection to reduce epileptic seizures, treatment of arteriovenous malformations in the brain, etc. In conventional methods, a dye is used to identify the target area 50. Positioning one or more devices 100 in a blood vessel adjacent to or surrounding the target area 50 allows monitoring of neural signals at the site where the device is deployed. Neural signals can be monitored before, during, and after injection of the dye to observe the effects of the dye or surgery.

[0061] In another variation, Figure 4BAs shown, the device described herein can replace or enhance the Wada test performed on epilepsy patients being considered for surgical treatment. The Wada test, also known as the internal carotid amobarbital test (ISAP), establishes the brain's language and memory representations in each cerebral hemisphere. In the test, which is performed while the patient is awake, a practitioner introduces a barbiturate (e.g., sodium amobarbital) into one of the internal carotid arteries via a cannula or intra-arterial catheter. The practitioner injects the drug once into either the right or left internal carotid artery, into one cerebral hemisphere, to inhibit that side of the brain. For example, if the drug is injected into the right carotid artery, the right side of the brain will be inhibited and unable to communicate with the left side of the brain. This allows the practitioner to observe the impact of any language and / or memory function on that hemisphere so that the other hemisphere can be evaluated. The test can also include an EEG recording to confirm that the affected side of the brain is inactive. The practitioner can then have the patient participate in language and memory-related tests. The present device can allow the device 100 to be positioned within a specific cytoarchitectonic area of ​​the brain (see Figure 2B ) to record activity while a physician performs various memory, language, or mental exercises that activate the brain. Detecting neural activity during testing allows mapping the location of the tasks within the brain. Once mapped, the physician can determine whether the area of ​​interest 50 can be treated / removed, and the potential consequences of doing so. Furthermore, device 100 can be used to monitor various areas of the brain during and after surgery.

[0062] In another variation, for example, Figure 4A and Figure 4B In the present invention, the device 100 can be placed in a specific cytoarchitectonic area of ​​the brain (see Figure 2B ), to aid in the safe intra-arterial or intravenous embolization of arteriovenous malformations or malignancies. The use of neuromonitoring during endovascular embolization procedures involves recording evoked potentials from the brain using scalp-based EEG technology. Somatosensory evoked potentials are triggered by electrical impulses delivered via electrical stimulation of the lower extremities and recorded from the sensory cortex via EEG. To ensure that the artery targeted for embolization does not supply the normal brain, an anesthetic such as lidocaine is injected into that artery. Any decrease in evoked potentials recorded during or immediately after the injection of lidocaine may represent potential brain damage that may occur if an embolic agent is subsequently injected into the target artery. Intracranial intravascular ECoG recordings have a higher sensitivity than scalp-based EEG and may represent an opportunity to improve the safety of neuromonitoring during arterial embolization procedures.

[0063] Figure 4A and Figure 4B The system described in is well-suited for intraoperative and postoperative patient monitoring, where the patient is barely moving, such that the microwires 120 can be extended from one or more incisions 8 in the individual 10 . Figure 5A variation of the system is shown that includes multiple microwire monitoring probes 100 coupled to one or more monitoring devices 130. Monitoring devices 130 may be fully or partially implanted within patient 10. Alternatively, monitoring devices 130 may be located external to the body, but allow coupling with probes 100 in a sterile manner. Figure 5 One of the purposes of the system shown is to provide in-patient or ambulatory monitoring of an individual 10. In this case, the probe 100 remains in a specific area of ​​the brain 12 for days or even months.

[0064] Figure 5 One application of the system shown involves monitoring patients with epilepsy, particularly those who have not responded positively to medication. In this case, any number of probes 100 are positioned within different areas of the brain 12. The probes 100 are connected to a monitoring device that communicates 150 with any number of electronic interface devices (e.g., a personal electronic device 140 or a computer system 120) via a wired or wireless connection. The patient 10 then stops taking medication for epilepsy for a period of time, during which time the system monitors brain activity through the probes 100. This activity is then analyzed to determine areas of the brain associated with epileptic seizures, including areas that were active before the seizure and / or areas that caused the seizure. The implanted system allows monitoring for days or even months. Current methods for determining areas of the brain associated with epileptic seizures involve craniotomy, a procedure that removes part of the skull or cranium to access areas of the brain. Figure 5 The system shown uses vascular access to perform brain region seizure mapping.In further variations, the systems described herein can be used in addition to conventional surgery.

[0065] The implanted unit 130 may include amplifiers, filters, controllers, data storage, power supplies, and wireless communication equipment (e.g., RF, Bluetooth, etc.) Such equipment allows data to be captured over relatively long periods of time to provide mobility for the individual while the assessment is being conducted.

[0066] In addition to brain mapping, the system described herein can provide a warning system for patients at risk of experiencing a seizure by maintaining an implant for a longer duration. For example, implant 100 can monitor various areas of the brain 12 and, if the system detects that an individual is at high risk for a seizure, provide a notification via an external device (e.g., 140) or via monitoring device 130. In this case, the patient can remain vigilant and avoid situations where a seizure poses an additional risk (e.g., driving, bathing, exercising, etc.). The system can also provide different levels of warning, such as low, medium, and high seizure risk, which would allow affected individuals greater flexibility in the event of a sudden, unexpected seizure.

[0067] In another variation, the system described herein can also be used as a neuromonitoring diagnostic system that detects electrophysiological biomarkers in patients with brain injury who are in an unresponsive state. Detection of biomarkers can be an indicator of patient recovery. Classen, J. (2019), “Detection of brain activation in unresponsive patients with acute brain injury,” New England Journal of Medicine, Vol. 380, No. 26, pp. 2497-2505. Classen, J. (2019). Detection of Brain Activation in Unresponsive Patients with Acute Brain Injury. The New England Journal of Medicine, 380(26) 2497-2505 ), an example of this response is discussed in the article .

[0068] For example, cases of coma, stroke, anoxic brain injury, or any brain injury that renders the patient clinically unresponsive. Using the system described herein, an ECoG response to external stimuli can be used to assess evidence of brain activation in an unresponsive patient, including auditory stimuli (e.g., verbal commands, familiar voices, etc.) and / or physical stimuli. In one variation, the purpose of the stimulation is to induce a change in brain state by interacting with the unresponsive patient. The neuromonitoring system can then provide a user interface / user interaction to the caregiver to provide the caregiver with various information about the patient's condition. For example, the user interface can provide a prediction of the efficacy of treatment, the degree of recovery, and / or measure the improvement of the unresponsive patient over time. The measured response to external stimuli can be compared with a dataset to predict the patient's recovery pattern. The dataset can be cloud-based and updated based on a machine learning algorithm that provides data normalization to provide a rating of the patient's condition, such as likely to improve or unlikely to improve.

[0069] Neuromonitoring systems can also be combined with provocative testing, in which a patient is monitored at rest to determine activity, and then again after anesthesia is administered to the patient or a specific area of ​​the patient's brain. Differences in the measured signals can be used as an indicator of brain function.

[0070] Using the system described herein as a neuromonitoring system allows one or more intravascular electrode arrays to be positioned, for example, in motor areas of the brain. However, the array (or arrays) can be located in any number of brain regions. Implantation of the electrode array can be temporary, wherein the array is removed after monitoring the patient. Alternatively, the array can be implanted chronically to increase monitoring of the patient. In either case, it may be desirable for the proximal end of the array to be directly coupled to a controller / transceiver / generator that is not implanted in the patient (e.g., see Figure 3 ).

[0071] Figure 6 Another application of the system described herein is shown in which the brain's distributed neural networks are used to improve technology control, motor control, sensory feedback, and communication with individuals. For example, Figure 6A magnified view of the brain 12 of an individual 10 is shown having any number of microwire probes 100 positioned within blood vessels 40 associated with specific discrete cytoarchitectonic regions of the brain 12 (e.g., C1, C19, and C42). Positioning the implant in discrete regions or networks of the brain allows for sensory stimulation or neural signal measurement in different areas of the brain to improve data communication with the individual. In the illustrated example, the cytoarchitectonic regions relate to the auditory, sensory, and visual regions of the brain 12. However, these regions have been selected for illustrative purposes only. Other variations of the systems and methods disclosed herein include any number of probes 100 positioned to be associated with any number of cytoarchitectonic regions of the brain.

[0072] like Figure 6 As shown, the probe 100 is coupled to a control unit 130 via microwires 102 extending through the additional vasculature 40. As described below, the probe 100 allows for data transmission to and from various regions of the brain 12 to provide improved information communication with the individual 10 and improved control of electronic devices networked with the probe 100 and the control unit 130. Figure 6 The regions shown are useful for data input to an individual. In other variations, the brain regions useful for data output from an individual may include the same or different brain regions. For example, these regions may include areas of the brain responsible for language, decision prediction, motor control, emotion, etc.

[0073] Figure 7 An example of the system described herein is shown in which a distributed neural network of an individual 10 is used to improve data communication between the individual 10 to improve interaction with any type of external device or machine 70. To explain the improved communication or data transmission, Figure 7 An aircraft or drone 72 and a car 74 are shown. Obviously, the present disclosure may include any machine or device configured for interacting with an individual 10.

[0074] In conventional systems, an operator controls the drone using a remote control device and an electronic interface that includes a screen that provides various data on the drone's operating parameters (e.g., speed, altitude, fuel, direction, etc.). The operator must observe these parameters in order to respond to any changes in the operating parameters. Next, the operator must conceive of thoughts for any subsequent actions, then formulate any corrective actions, and the operator must implement the actual actions that provide the corrective actions for the drone. While the operator may perform these actions quickly, there is a time delay between the drone's condition changing, observing the change in condition, and then implementing the actual corrective actions to control the drone. The speed of reaction of the vehicle operator requires that thoughts travel from their origin in the cerebral cortex through the spinal cord, peripheral nerves, and ultimately trigger muscle activity to realize the will command. Device ( Figure 5 ) can transmit information at a much faster rate than an unmodified human body.

[0075] In the system, such as Figure 7 As shown, data 64 regarding the operating parameters of the drone can be transmitted to the network 62 or directly to the electronics 140 that interfaces with the control unit 130 of the system described herein. (As mentioned above, for all examples discussed herein, the use of a separate electronics unit 140 is optional.) As mentioned above (see Figure 6 ), various probes can be positioned at different cytoarchitecture regions, allowing the information 62 transmitted to the individual to trigger stimulation of specific cytoarchitecture regions. For example, if the drone is gaining altitude, the system can stimulate one brain region, and if the drone is losing airspeed, the system can stimulate a second brain region. The operator will be trained to recognize the various stimuli and respond accordingly. This direct data transmission from the machine 70 to the system and individual 10 allows for high-fidelity control of the drone.

[0076] Furthermore, the system can allow individual 10 to use brain activity generated in specific cytoarchitecture regions to issue control commands to a drone. For example, if individual 10 determines that the drone needs a course correction (e.g., moving to the right), an implant positioned in the individual's motor area will pick up the individual's brain activity (e.g., pushing down with the right foot or activating muscles on the right side), enabling the individual to generate the thought of a motor activity on the right side. This neural activity is then transmitted via data 62, either over network 60 or directly to drone 72, which receives data 64 and automatically corrects its course. In both examples described herein, the system allows direct communication between discrete brain regions and an external machine 70 requiring control. This system allows for improved control of the machine 70 and improved perception of the machine's operating conditions. While the above description discusses the use of cytoarchitecture regions that control motor activity, any number of cytoarchitecture regions can be used, including but not limited to regions that control emotional communication, language, decision-making prediction, visual-spatial perception, auditory perception, and sensory perception (e.g., touch, smell, taste, etc.).

[0077] In yet another variation, Figure 7 The system shown can use artificial intelligence or external data generated by the network 60 independently of the machine 70 or data indirectly from the machine. For example, if an implant is positioned in a sensory area of ​​the brain, triggering the implant can produce a perception of smell, taste, or similar sensory feedback associated with a warning of a predetermined condition. As an example, if the individual 10 is in a hostile area and the drone 72 or satellite has identified an actual risk area or a potential risk area, the implant can be triggered to produce a specific perception associated with the actual risk area or the potential risk area. When the individual moves toward the area, the perception can be triggered to increase, and when the individual leaves the area, the perception decreases. Alternatively or additionally, this additional data can be used to feedback the location of the enemy through the visual cortex and presented on a geospatial representation through the brain of the individual 10 to produce direct visual feedback from the control station to the brain.

[0078] Figure 8 Another variation of using a distributed neural network to improve data communication with an individual 10 is shown. In this variation, implanted microwire sensors can be placed in the brain region corresponding to the prefrontal cortex, which is responsible for decision-making. Thus, the implanted probes can generate a signal predicting decision-making. This feature can be used when an individual 10 is faced with making a difficult decision (e.g., a soldier, law enforcement officer, firefighter, etc.). The system can transmit data 66, 68 to a monitoring station 80, which attempts to actually predict how the individual will make a decision and can then work with the individual to assist, help, or even prevent that behavior.

[0079] In another variation, tactical personnel, such as astronauts, who have limited communications with base command while on mission, utilize the system for enhanced communications (e.g., with another astronaut or a dispatch center). Figure 5 ) can monitor astronauts across distributed cognitive domains that aid in decision making ( Figure 2B )'s real-time cognitive activity. For example, emotional arousal transmission, decision prediction, and motor function can be monitored. The dispatch center or additional individuals can further provide information to the individual's cognitive domain, which can be received through various forms of perception, including sensation, hearing, vision, and smell. For example, geospatial information to aid decision-making during a mission can be provided directly to the visual cortex, and auditory feedback directly to the auditory cortex. Astronauts can then utilize this direct flow of information to and from the cerebral cortex to execute their mission with greater precision.

[0080] Figure 9 Another variation of using a distributed neural network is shown by creating a brain-to-brain network between at least two individuals 10, 11, in which each individual has a microwire monitoring / stimulation probe 100 positioned in a specific cytoarchitectonic region of their respective brains. For illustrative purposes, Figure 9 Two individuals 10, 11 are shown. However, the present disclosure may include any number of individuals. As described herein, data transmission 66 and 68 between the individuals may rely on the network 60, or may be performed directly through a local or private network. Also as discussed, the system may include one or more electronic devices 140, 142 that communicate with the control units 130, 132 of the coupled probes, or the electronic devices 140, 142 may be integrated into the control units 130, 132, respectively. Figure 9 The illustrated example allows for any number of ways to link two individuals 10, 11, depending on the placement of the device, particularly within the cytoarchitectonic regions of the brain. In one example, an implant can be located in an area of ​​the brain responsible for emotional responses, allowing each individual to be aware of the emotional components of the other. This networking is not limited to emotions and can include connecting any area of ​​the brain to provide direct sensory, motor, language, auditory, visual, taste, olfactory, and other data communication between individuals.

[0081] In a variation, a team of personnel performing a tactical mission leveraged networked brain functions to achieve a higher level of information flow across the team. Being able to coordinate like a single, interconnected organism enabled enhanced team capabilities to achieve a common goal. In one example, the blinding flash produced by an explosion was visible not only to the direct witnesses of the blast, but also to the entire team. Injury to one team member affected the entire group. Shared awareness across cognitive domains enabled the team to perform at a higher level of function.

[0082] Note that the above Figures 7 to 9 Shown as separate applications, combining each application or portions of each application is within the scope of the present disclosure.

[0083] In addition to the applications described above, the neural interface system described herein could provide individuals with severe paralysis with an implantable brain-computer interface (BCI) and, compared to the current standard of care, enhance their autonomy by restoring their ability to perform daily living functions and activities with minimal caregiver intervention. Therefore, the BCI system described herein may require "always-on" functionality. For battery-powered systems, minimizing power consumption is a top priority, as charging requires caregiver assistance. Furthermore, the BCI system may require continuous streaming data to provide the user with low-latency control of the target device.

[0084] Conventionally, implementing “always-on” functionality in a battery-powered system is difficult due to the high power consumption of BCI recording hardware and decoding algorithms.

[0085] The system described herein can alleviate concerns associated with an "always on" system because it is already accessing the user's neural data. Thus, variations of the system described herein can provide different operating configurations based on the user's activity. For example, the operating configurations can include varying energy consumption states, such that one operating configuration is a low-power usage configuration. The BCI can select this configuration through the user using a control interface or automatically enter this low-power usage state if the system is already monitoring the user's neural activity.

[0086] For example, the systems described herein can adjust a neural interface by monitoring an individual's neural activity. The neural interface can include a neural monitoring device (e.g., an implant described herein) operably connected to a control unit. The operably connected may include a hardwired connection, a wireless connection, infrared, sound, and / or vibration. The control unit can be configured to generate an output control signal for interacting with an external electronic device. Variants of the control unit include an implanted control unit or an external telemetry unit. One variation of the system and / or method includes: providing a signal from a neural monitoring device implanted in an individual to the control unit, wherein the signal represents the individual's neural activity, and wherein detection of a predetermined neural activity causes the control unit to generate an output control signal; determining an activity level of the individual by monitoring the individual's neural activity; and wherein the control unit is configured to adjust the neural interface from a first operating configuration to a second operating configuration upon determining that the activity level satisfies a first predetermined condition, wherein power consumption of the neural interface in the first operating configuration is different from power consumption of the neural interface in the second operating configuration.

[0087] In one variation, the first predetermined condition includes the individual's sleep state, and determining the activity level includes determining the individual's sleep state by evaluating neural activity against a neural sleep indicator. Because the BCI system already has access to the individual's neural signals, the system can monitor neural data that is not present when the user is awake. For example, neurophysiological phenomena such as K-complexes and sleep spindles occur during the early stages of sleep. Therefore, using neural data to detect when the user is asleep can be used to switch any device to a lower energy usage state.

[0088] Alternatively or in combination, the first predetermined condition comprises a failure to generate the output control signal within a predetermined time period.

[0089] The control unit may be further configured to adjust the neural interface from the first operating configuration to the second operating configuration when the output control signal is associated with an idle command instruction.

[0090] Variations of the systems and / or methods include a neural interface configured to provide perceptible feedback to the individual indicating whether the neural interface is in the first operating configuration or the second operating configuration. The systems and / or methods may provide a neural interface configured to allow the individual to maintain the neural interface in the first operating configuration.

[0091] In a further variation, the control unit may be further configured to send an idle signal to the external electronic device upon or before adjusting to the second operating configuration.

[0092] Another variation of the method and / or system includes determining an activity level of the individual by monitoring the individual's neural activity while the neural interface is in a second operating configuration, and wherein the control unit is further configured to adjust the neural interface from the second operating configuration to the first operating configuration upon determining that the activity level satisfies a second predetermined condition.

[0093] The control unit may be further configured to adjust the neural interface from the second operating configuration to the first operating configuration when the output control signal is associated with the activity command instruction. In addition, the control unit may be configured to adjust the neural interface from the second operating configuration to the first operating configuration when the individual generates at least one output control signal.

[0094] Another variation of the method and / or system includes changing the communication frequency in the neural interface by monitoring neural activity of the individual. The method and / or system may include: providing a signal from a neural monitoring device implanted in the individual to a control unit, wherein the signal represents the neural activity of the individual, and wherein detection of predetermined neural activity causes the control unit to generate an output control signal; determining an activity level of the individual by monitoring the neural activity of the individual; and wherein the control unit is configured to change the neural interface from a first operating configuration to a second operating configuration upon determining that the activity level satisfies a first predetermined condition, wherein the communication rate in the first operating configuration is different from the communication rate in the second operating configuration.

[0095] When in the "idle" state, the BCI can perform the minimum amount of recording and calculations required to provide a single switching output, which may be much slower than the normal switching output produced in the "active" state. For example, in the "active" state, the BCI can sample all electrode channels and stream all recorded data to the decoding algorithm. When in the "idle" state, the BCI can sample a smaller subset of electrode channels and only stream data at a lower duty cycle (e.g., 10%).

[0096] Visual and / or auditory feedback can also be provided to the user to indicate the BCI status, and this visual feedback can be synchronized with the data transmission duty cycle to make it easier for the user to wake up. For example, a visual indicator can show the user that their device is currently in "idle" mode, and a countdown timer or timed radial can be displayed to show the user the correct moment when the wake-up switch will become available. In the absence of visual feedback, the user can repeatedly generate the switch output until they observe that "active" functionality has been restored.

[0097] The wake-up switching feature can be implemented only in software and is user-configurable. Thus, the user can decide whether a lower operating state is desired. If not, the feature can be disabled and the BCI will always be in "active" mode.

[0098] Identifying a user's activity level can also allow the system to control external devices that are not part of the neural interface or BCI. For example, in a smart home, the neural interface can interface with the home's control system to control various items, such as turning off all the lights in the house, ensuring that the doors are locked, or even controlling any desired soundscapes that may improve the user's sleep quality.

[0099] The BCI system can be configured so that the individual has a continuous connection for an extended period of time. This avoids the need for a caregiver to disconnect the individual from the BCI system or connect the individual to the BCI system. For example, the BCI system can include a charging mechanism that powers the BCI system for an increased duration (e.g., 6 hours). In another variation, the BCI system is configured with an "idle mode" to reduce the current drain on the battery. In "idle mode," the individual can activate the system or exit "idle mode" without the assistance of a caregiver. Additionally, allowing the BCI system to be conveniently charged or automatically charged will increase the duration of the continuous connection. In this case, the BCI system allows one or more components of the system to be positioned in a position that allows the components to be recharged.

[0100] Another benefit of continuous connection and recharging is minimal caregiver intervention. In this scenario, a caregiver would only need to be present once a day to assist with charging or check the BCI. This can be achieved by leaving the charger in place and incorporating firmware updates into the charger via a mobile app. The firmware needs to be able to power the charger on and off without a physical button.

[0101] Various aspects of the above systems can support (at least intermittent) independent communication for patients.

[0102] In another variation, the BCI system may include one or more dashboards that provide details about the BCI's operational history. Such a dashboard may include a monitor in electrical communication with the BCI, or may include data transmitted by the BCI to a server or network, such that the BCI's operational history is available via a portable electronic device or other website. This allows individuals and caregivers, as well as interested parties (e.g., relatives of the individual), to observe BCI operation. This allows multiple people to monitor an individual's activities. For example, a dashboard may display historical information about the system's operation (e.g., when the system was in autonomous mode or when it left autonomous mode). While a caregiver cannot be prevented from turning off the BCI, a clinician or other family member will be able to see on a timeline whether part or all of the system was previously disabled.

[0103] Variations of the BCI systems described herein that allow for increased autonomy include low-calibration systems, which are a measure of how easily a user can begin using a BCI system after a period of inactivity. Calibration can be quantitatively assessed by measuring the time required to calibrate a BCI system to a user and make it available for use. For example, a low-calibration BCI system would be one that takes no more than thirty (30) seconds between activation (e.g., powering on, exiting idle mode) and being available for use.

[0104] In one variation, a low calibration BCI system will include a minimal number or no external hardware components that need to be positioned on or to the patient and connected to the BCI system to allow the system to operate as intended. For example, the above-described system is implanted or coupled to an individual and can be electronically activated from an idle mode or off mode to start the BCI system. As described above, a system comprising minimal components includes: a charger for an implanted receiver / transmitter unit, an SCU, and a screen / device, all of which are wirelessly connected. In contrast, systems requiring external hardware, such as an eye tracker device, require the paralyzed user to be physically located in front of the eye tracker hardware.

[0105] The systems and methods described herein provide restoration of autonomy to patients, including those with severe movement disorders. Thus, these systems and methods provide BCIs that are: continuously available; provide independent system activation; minimal calibration; require no wearable component or hardware adjustments; and provide greater decision-making power for the individual.

[0106] In another variation, the autonomy-enhancing BCI system includes a system with low latency, where latency is measured as the time between presentation of a prompt (e.g., indicating that the individual should select an action on the BCI) and the individual triggering the action (e.g., the time between presentation of an option and the individual "clicking" the option). In other words, the individual is able to generate more clicks in any time period, which supports the user to remain more engaged and / or engaged for longer periods of time. U.S. Provisional Application No. 63 / 480,746, filed on January 20, 2023, the contents of which are incorporated herein by reference, discusses brain-computer interfaces, systems, and methods for controlling a device based on detection of transient oscillations or pseudo-oscillation bursts ( brain-computer interfaces, systems and methods for controlling a device based on the detection of transient oscillatory or pseudo-oscillatory bursts ). A system using detection of transient oscillations or pseudo-oscillation bursts can provide a low latency system.

[0107] Such an autonomous BCI system will also require high accuracy, where the accuracy of the system can be measured by the rate at which the BCI system generates actions initiated by the individual and does not initiate any action when the individual does not initiate an action.

[0108] As described above, the mechanism of action of the implanted MNP in a BCI system can use the detection of an individual's motor intention and translate that motor intention into an alternative control signal to enable the individual to perform a functionally meaningful output task. Therefore, the core performance indicator of the MNP and BCI system should represent its ability to reliably convert neural motor intention into a digital output. This can be considered a digital motor output (DMO). The DMO carrying motor intention information can be mapped to specific or general computer actions that can be used to control a personal computer or device. For example, Figure 10 As shown, the implanted probe 100 and internal transmission unit 130 can translate the neuromotor intent of the individual 100 to the electronic device 120, which provides any number of general computer actions 18a-18d to directly control the device 120 or allow the device 120 to further control the auxiliary device 12a. In the illustrated variation, the transmission 150 occurs via an external system control unit 140, however, the system can use direct transmission. The ability of the implantable MNP BCI 100 / 13 to generate reliable DMO makes it a device-independent clinical measurement method.

[0109] The goal of evaluating the efficacy of any MNP using performance metrics for assistive computer actions (e.g., typing) can be hampered by variables in the operating system and software variability for each computer action use case. For example, adding predictive or generative text features to an MNP's operating system may lead to inconsistent assessments of the MNP's fundamental efficacy and utility. In contrast, creating a metric structure around the DMO itself represents an implicitly valid and reliable approach to assessing the fundamental utility of any MNP. For example, a set of objective performance metrics to assess the extent to which any emerging MNP can generate the DMO should capture the DMO's reliability in a manner that reflects the individual's intended application. This can be achieved by assessing DMO accuracy across a sufficient number of task repetitions using a task that captures fundamental DMO performance, performed at appropriately selected time points after implantation or activation. Accuracy is equal to the number of correct trials divided by the total number of trials.

[0110] In further variations, the present disclosure includes BCI systems with subsystems that can be decoupled from the "full system," where the full system provides additional functionality / interaction to the patient, but the subsystems allow the patient to call for help at any time. "Functionality in component." For example, in Figure 10In , the complete system includes the electronic device 120 (optionally controlling additional equipment or simply a computer), the external system control unit 140 (optionally interfacing between the individual 100 and the electronic device 120), and the implanted components, such as 100 and 130. In practice, the system may also include additional components that enhance the individual's ability to interact with the device but require a significant amount of time to set up / remove. For example, many BCI systems employ eye tracking devices. The ability of a BCI system to operate as a subsystem provides individuals (especially those who are fully or partially paralyzed) with the ability to interact with a caregiver using the subcomponents while the additional components are removed. This is particularly useful when the individual is separated from the system during rest periods, or when the individual is unable to use the complete BCI system and components.

[0111] Thus, the present disclosure includes a brain-computer interface system for increasing the autonomy of an individual in interacting with an electronic device, wherein the individual is fully or partially paralyzed. For example, such a brain-computer interface system may include a neural monitoring device coupled to the individual and configured to detect neural activity from the individual. For example, Figure 10 Shown are implant 100 and internal transmission / control unit 130 operably coupled to a system control unit 140 operably coupled to nerve monitoring device 100 and removably coupled to individual 100 .

[0112] The present disclosure also includes a method for using a brain-computer interface to enhance the autonomy of an individual, wherein the individual is fully or partially paralyzed. For example, the method may include: positioning a neural monitoring device in or on the individual, the neural monitoring device configured to detect neural activity from the individual; disconnecting a control unit from the individual, wherein the control unit is configured to be operably coupled to the neural monitoring device and configured to interact with one or more electronic devices when the individual generates neural activity; and connecting the neural monitoring device to an electronic network such that the individual maintains the ability to communicate with the electronic network using the neural activity.

[0113] Another variation of a brain-computer interface system for increasing the autonomy of an individual in interacting with an electronic device, wherein the individual is fully or partially paralyzed, the brain-computer interface system comprising: a neural monitoring device coupled to the individual and configured to detect neural activity from the individual; a control unit operably coupled to the neural monitoring device and removably coupled to the patient, wherein the control unit is configured to interact with the electronic device when the individual generates neural activity; and wherein the control unit is further configured to electronically communicate with an electronic network such that when the electronic device is disconnected from the individual, the individual is still able to communicate with the electronic network using the neural activity.

[0114] The system control unit 140 is configured to interact with the electronic device 120 when the individual generates neural activity; and wherein the neural monitoring device 100 is further configured to electronically communicate with an electronic network, such as directly and wirelessly communicating with a cloud server, or communicating with the system control unit 140 via a wireless connection, such that when the control unit 140 is disconnected from the individual, the individual is still able to communicate with the electronic network using the neural activity. The wireless connection may include a WIFI connection, Bluetooth, RFID, etc. In another variation, the use of the system control unit 140 is optional, wherein the internal control unit 130 is configured to wirelessly engage the electronic device 120 and / or cloud server. In another variation, the neural monitoring devices 100, 130 are configured to electronically communicate with the electronic network independently of the control unit 140.

[0115] All prior subject matter (e.g., publications, patents, patent applications) mentioned herein is incorporated by reference in its entirety, except to the extent such subject matter conflicts with the subject matter of the present invention, in which case the disclosure herein controls. Items cited are provided solely for their disclosure prior to the filing date of the present application. Nothing herein should be construed as an admission that the present invention is not entitled to an advantage by virtue of prior invention.

[0116] References to singular items include the possibility that there are multiple identical items. More specifically, as used herein and in the appended claims, the singular forms "a," "an," "said," and "the" include plural referents unless the context clearly dictates otherwise. It should also be noted that claims can be drafted to exclude any optional elements. Therefore, this statement is intended to serve as a prerequisite for the use of exclusive terms such as "only," "only," and the like, as well as in the recitation or "negative" limitation of claim elements. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0117] In understanding the scope of this disclosure, the terms "comprise" and its derivatives as used herein are intended to be open-ended terms that specify the presence of stated features, elements, components, groups, wholes, and / or steps, but do not exclude the presence of other unstated features, elements, components, groups, wholes, and / or steps. The foregoing also applies to words with similar meanings, such as the terms "comprising," "having," and their derivatives. Moreover, when used in the singular, the terms "part," "portion," "member," "element," or "assembly" can have dual meanings of a single part or a plurality of parts. As used herein, the following directional terms "forward, rearward, above, downward, vertically, horizontally, below, transversely, laterally, and vertically" and any other similar directional terms refer to those positions of a device or piece of equipment or those directions in which a device or piece of equipment is translated or moved. Finally, as used herein, terms of degree such as "substantially," "approximately," and "approximately" refer to a reasonable amount of deviation from a specified value (e.g., up to 0.1%, 1%, 5%, or 10%, as such variations are appropriate) such that the end result does not change significantly or substantially.

[0118] The present disclosure is not intended to be limited to the scope of the particular forms set forth, but is intended to cover alternatives, modifications, and equivalents of the variations or embodiments described herein. In addition, the scope of the present disclosure fully encompasses other variations or embodiments that become apparent to those skilled in the art in light of this disclosure.

Claims

1. A method of adjusting a neural interface by monitoring neural activity of an individual, the neural interface comprising a neural monitoring device operably connected to a control unit, the control unit being configured to generate an output control signal for interacting with an external electronic device, the method comprising: providing a signal from the neural monitoring device implanted in the individual to the control unit, the signal representing neural activity of the individual, and detection of predetermined neural activity causing the control unit to generate the output control signal; determining an activity level of the individual by monitoring neural activity of the individual; and in, The control unit is configured to adjust the neural interface from a first operating configuration to a second operating configuration upon determining that the activity level satisfies a first predetermined condition, the power consumption of the neural interface in the first operating configuration being different from the power consumption of the neural interface in the second operating configuration.

2. The method according to claim 1, wherein: The first predetermined condition comprises a sleep state of the individual, and determining the activity level comprises determining the sleep state of the individual by evaluating the neural activity against a neural sleep index.

3. The method according to claim 1, wherein: The first predetermined condition includes a failure to generate the output control signal within a predefined time period.

4. The method according to claim 1, wherein: The control unit is further configured to adjust the neural interface from the first operating configuration to the second operating configuration when the output control signal is associated with an idle command instruction.

5. The method according to claim 1, wherein: The neural interface is configured to provide perceptible feedback to the individual to indicate whether the first operating configuration or the second operating configuration.

6. The method according to claim 1, wherein: The neural interface is configured to allow the individual to maintain the neural interface in the first operating configuration.

7. The method according to claim 1, wherein: The control unit is further configured to send an idle signal to the external electronic device when or before adjusting to the second operating configuration.

8. The method according to claim 1, further comprising: The activity level of the individual is determined by monitoring the neural activity of the individual when the neural interface is in the second operating configuration, and wherein the control unit is further configured to adjust the neural interface from the second operating configuration to the first operating configuration when it is determined that the activity level satisfies a second predetermined condition.

9. The method according to claim 8, wherein: The control unit is further configured to adjust the neural interface from the second operating configuration to the first operating configuration when the output control signal is associated with an active command instruction.

10. The method according to claim 8, wherein: The control unit is further configured to adjust the neural interface from the second operating configuration to the first operating configuration when the individual generates at least one output control signal.

11. A method of changing a communication frequency in a neural interface by monitoring neural activity of an individual, the neural interface comprising a neural monitoring device, the neural monitoring device being operably configured to communicate with a control unit at a communication rate, and the control unit being configured to generate an output control signal for interacting with an external electronic device, the method comprising: providing a signal from the neural monitoring device implanted in the individual to the control unit, the signal representing neural activity of the individual, and detection of predetermined neural activity causing the control unit to generate the output control signal; determining an activity level of the individual by monitoring neural activity of the individual; and Wherein, the control unit is configured to change the neural interface from a first operating configuration to a second operating configuration when it is determined that the activity level meets a first predetermined condition, and a communication rate in the first operating configuration is different from a communication rate in the second operating configuration.

12. A method for improving the autonomy of a paralyzed individual in operating an external electronic device, the method comprising: providing a brain-computer interface configured to monitor neural activity of the paralyzed individual, the brain-computer interface comprising a neural monitoring device operably connected to a control unit, the control unit configured to generate an output signal for interacting with the external electronic device; wherein the brain-computer interface is configured to enter an idle mode, wherein the brain-computer interface consumes less power in the idle mode than in the active mode; and An activation signal is received from the paralyzed individual to switch the brain-computer interface from the idle mode to an active mode without assistance from a caregiver.

13. The method according to claim 12, further comprising: The control unit and the external electronic device are coupled to reduce calibration time of the brain-computer interface when entering the active mode.

14. The method according to claim 13, wherein: The connection between the control unit and the external electronic device occurs wirelessly.

15. The method according to claim 12, wherein: The brain-computer interface is configured to be connected by the paralyzed individual to a rechargeable power source.

16. The method according to claim 12, wherein: The brain-computer interface is configured to transmit operational data from the brain-computer interface to a remote electronic dashboard, which allows an individual to monitor the activity of the brain-computer interface.

17. The method according to claim 16, wherein: The brain-computer interface is configured to wirelessly transmit operational data from the brain-computer interface to the remote electronic dashboard.

18. The method according to claim 12, wherein: The brain-computer interface is configured to have a latency of five seconds or less.

19. The method according to claim 12, wherein: The brain-computer interface is configured to allow the paralyzed individual to initiate calibration of the brain-computer interface upon entering the active mode.

20. A method for improving the autonomy of a paralyzed individual in operating an external electronic device, the method comprising: Providing a brain-computer interface configured to monitor the neural activity of a paralyzed individual, the brain-computer interface comprising a neural monitoring device operably connected to a control unit, the control unit being configured to generate an output control signal for interacting with the external electronic device in response to the neural activity of the paralyzed individual, the neural activity of the paralyzed individual being associated with a prompt signal generated by the brain-computer interface; and The brain-computer interface is calibrated within a minimum time period, wherein calibrating the brain-computer interface allows the paralyzed individual to activate the output control signal after the paralyzed individual has not used the brain-computer interface for a period of time.

21. A method for improving the autonomy of a paralyzed individual in operating an external electronic device, the method comprising: A brain-computer interface configured to monitor neural activity of a paralyzed individual is provided, wherein the brain-computer interface includes a neural monitoring device operably connected to a control unit, the control unit being configured to generate an output control signal for interacting with the external electronic device when the paralyzed individual generates neural activity in response to a prompt generated by the brain-computer interface, the brain-computer interface including a high-precision interface ratio, which is a measure between intentional neural activity associated with the prompt and neural activity not associated with the prompt.

22. The method according to claim 21, wherein: The high-precision interface ratio includes 95%.

23. A brain-computer interface for improving the autonomy of a paralyzed individual in operating an external electronic device, the brain-computer interface comprising: a neural monitoring device configured to detect neural activity of the paralyzed individual; a control unit operably connected to the neural monitoring device, the control unit being configured to generate a prompt on a display, the prompt being associated with one or more commands, and when the paralyzed individual generates neural activity associated with an intention to select the prompt, the control unit generating an output control signal for interacting with the external electronic device; and Wherein, the control unit is configured to generate the prompt and the output control signal within a minimum time.

24. The brain-computer interface according to claim 23, wherein: The minimum time is comprised of 5 seconds.

25. A brain-computer interface system for increasing the autonomy of an individual interacting with an electronic device, the individual being fully or partially paralyzed, the brain-computer interface system comprising: a neural monitoring device coupled to the individual and configured to detect neural activity from the individual; a control unit operably coupled to the neural monitoring device and removably coupled to the individual, the control unit configured to interact with the electronic device when the individual generates the neural activity; and Wherein, the neural monitoring device is further configured to electronically communicate with an electronic network, so that when the control unit is disconnected from the individual, the individual is still able to communicate with the electronic network using the neural activity.

26. The brain-computer interface system according to claim 25, wherein: The nerve monitoring device includes an implant configured to be positioned near or in neural tissue and an internal unit in electrical communication with the implant.

27. The brain-computer interface system according to claim 25, wherein: The nerve monitoring device is configured to electronically communicate with the electronic network independently of the control unit.

28. The brain-computer interface system according to claim 25, wherein: The nerve monitoring device is configured to electronically communicate with the electronic network using the control unit.

29. A brain-computer interface system for increasing the autonomy of an individual interacting with an electronic device, the individual being fully or partially paralyzed, the brain-computer interface system comprising: a neural monitoring device coupled to the individual and configured to detect neural activity from the individual; a control unit operably coupled to the neural monitoring device and removably coupled to the individual, the control unit configured to interact with the electronic device when the individual generates the neural activity; and Wherein, the control unit is further configured to electronically communicate with an electronic network, so that when the electronic device is disconnected from the individual, the individual can still communicate with the electronic network using the neural activity.

30. A method of using a brain-computer interface to increase the autonomy of an individual who is fully or partially paralyzed, the method comprising: positioning a neural monitoring device in or on the individual, the neural monitoring device configured to detect neural activity from the individual; decoupling a control unit from the individual, wherein the control unit is configured to be operably coupled to the neural monitoring device and configured to interact with one or more electronic devices when the individual generates the neural activity; as well as The neural monitoring device is coupled to an electronic network such that the individual retains the ability to communicate with the electronic network using the neural activity.

31. The method according to claim 30, wherein: Coupling the nerve monitoring device to the electronic network includes coupling the nerve monitoring device to the electronic network using the control unit when the control unit is detached from the one or more electronic devices.

32. The method of claim 30, wherein: Coupling the nerve monitoring device to the electronic network includes coupling the nerve monitoring device to the electronic network without using the control unit.

33. The method of claim 30, wherein: Coupling the nerve monitoring device to the electronic network includes decoupling a control unit from the individual.

34. The method of claim 30, wherein: The nerve monitoring device includes an implant configured to be positioned near or in neural tissue and an internal unit in electrical communication with the implant.

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