Apparatus, method, and system of measuring neurological signals from peripheral nerves and interfacing with the brain

Abstract

A wearable brain-computer that is interfaced through a peripheral nervous system. A method and system for measuring a neurofeedback signal by: generating an input signal; providing the input signal to a peripheral nervous system; allowing the input signal to propagate through the peripheral nervous system; and receiving the neurofeedback signal from the peripheral nervous system.

Description

APPARATUS, METHOD, AND SYSTEM OF MEASURING NEUROEOGICAE SIGNAES FROM PERIPHERAE NERVES AND INTERFACING WITH THE BRAINFIEED

[0001] This invention is in the field of neurological signal measurement, and more specifically to wearable brain-computer that is interfaced through a peripheral nervous system.BACKGROUND

[0002] U.S. Pub. No. 2019 / 0223747 to Chou discloses a wearable physiological activity sensor, sensing device, and sensing system, which employs at least an ear-worn device to install physiological sensing element(s), thereby acquiring physiological signals from the head and / or the ear(s) of a user. The sensor, sensing device, and sensing system also can be used to perform procedure(s) capable of influencing the user’s physiological state in accordance with the physiological signals.

[0003] U.S. Pat. No. 10,694,946 to Freer et al. discloses a method and device for detecting EEG signals of a first person in proximity to the device. The device can include a non-contact EEG directional circuit having non-contact sensors, the non-contact EEG directional circuit being configured to detect the EEG signals produced by a brain of the first person without making contact with the first person. The device can further include a processor coupled to the non-contact EEG directional circuit that is configured to analyze the EEG signals to detect patterns in the EEG signals that correspond to a state of the first person in proximity to the non-contacting sensor andfeedback device that is configured to provide a second person with an indication of the state of the first person in proximity to the non-contacting sensor. Additionally, the device can include a contact EEG circuit having sensors that are in contact with the second person and that is configured to detect second EEG signals produced by a brain of the second person, wherein the processor is coupled to the contact EEG circuit and is configured to analyze the second EEG signals to detect patterns in the second EEG signals that correspond to a state of second the person.

[0004] U.S. Pat. No. 9,953,650 to Falevsky discloses biofeedback to alter subsequent speech of one or more participants engaged in a discussion. Biofeedback signals can range from simplistic (beeps, flashes, vibrations, etc.) to more complicated images, videos, and music. The bio-feedback signals can be rendered to the participant(s) based on the extent to which the discussion relates to one or more goals. Signals can be rendered in any suitable manner, including a visual image rendered by a virtual reality headset or other device, an electronically generated auditory sound, other tactilely perceptible vibrations or other movements, preferably in substantially near realtime.

[0005] U.S. Pat. No. 11,253,188 to Fass discloses a personalized biofeedback computerized system, an End-to-End eHealth smart platform for analysis, diagnosis and therapy of types of behavioral disorders. The system comprises a Captive Portal (CP) data input for initial input data and for continuous input data, a database comprising data, a Computer Processing Manager (CPM) for processing the patient data and the database, a Graphical User Interface (GUI) for interfacing with a user, and an Electroencephalography (EEG) or hemoencephalography (HEG) cap for stimulating predetermined areas in the brain, wherein the CPM is interconnected to the CPP, the database and the GUI, the CPM provides instructions for cranial electrode mediated stimulation to the areas in the brain according to a predetermined patient data dependent protocol, and thedatabase provides external data. A preferred embodiment of the invention is a multilayered biofeedback system.SUMMARY

[0006] A peripheral apparatus for brain to computer interface communications to monitor and respond to brainwaves. The system comprises three main components: a brainwave sensor for monitoring brain activity, an effector that responds to brainwave signals, and a controller for the operational control of computer-based systems.

[0007] According to an aspect, a method is provided for measuring a neurofeedback signal that comprise of: generating an input signal; providing the input signal to a peripheral nervous system; allowing the input signal to propagate through the peripheral nervous system; and receiving the neurofeedback signal from the peripheral nervous system. The method may modulate a carrier signal with at least one of: white noise or data to modulate the input signal. The modulating may be at least one of: a spread spectrum modulation, a pulse modulation, an amplitude modulation, and a frequency modulation. The method may further record the neurofeedback signal on a memory. The neurofeedback signal may comprise at least one of: gamma waves, beta waves, alpha waves, theta waves, and delta waves. The method may process the neurofeedback signal to determine at least one of: gamma waves, beta waves, alpha waves, theta waves, and delta waves.

[0008] According to an aspect, a system is provided for measuring neurofeedback signals that comprise of: a transmitter system coupled to a peripheral nervous system; a receiver system coupled to the peripheral nervous system; a processor configured to execute instructions from a computer-readable memory, the instructions comprising: generating an input signal; providing the input signal to the transmitter system; waiting for the input signal to propagate through theperipheral nervous system; and receiving the neurofeedback signal from the receiver system. The transmitter system may comprise a digital-to-analog converter receiving input signal instructions from the processor and an emitter providing the input signal to the peripheral nervous system. The transmitter system may further comprise of a white noise generator modulating with the input signal. The transmitter system may further comprise a modulator configured to modulate a continuous carrier signal with the input signal. The modulator may be configured to perform at least one of: a spread spectrum modulation, a pulse modulation, an amplitude modulation, and a frequency modulation. The input signal may suppress pain at or near a location of the transmitter system. The system may further comprise instructions to record the neurofeedback signal on the computer-readable memory. The neurofeedback signal may comprise at least one of: gamma waves, beta waves, alpha waves, theta waves, and delta waves. The system may further comprise instructions to process the neuro feedback signal to determine at least one of: gamma waves, beta waves, alpha waves, theta waves, and delta waves. The system may further comprise instructions to execute at least one computer command in response to the neurofeedback signal.

[0009] The system according to claim 7, wherein the instructions further comprise: receiving an interaction from a brain through the neurofeedback signal; and transmitting the interaction over a body area network that may connect to a computer network, Internet, or cloud networkDESCRIPTION OF THE DRAWINGS

[0010] While the invention is claimed in the concluding portions hereof, example embodiments are provided in the accompanying detailed description which may be best understood in conjunction with the accompanying diagrams where like parts in each of the several diagrams are labeled with like numbers, and where:

[0011] Figure 1 is a model of peripheral neurofeedback communication with illustrations of signals being transmitted and data being acquired.

[0012] Figure 2 is a conceptual diagram of a sensory - motor pathway that modulation signals propagate along - the skin and dorsal root to be sent to a brain.

[0013] Figure 3 is a block diagram of modulation methods that can be used for neurofeedback system through peripheral nerves.

[0014] Figure 4 is an illustration of the resistive-capacitive (RC) circuit between electrodes and nerves.

[0015] Figure 5 illustrates the electrode placement and details of the hardware steps for signal processing.DETAILED DESCRIPTION

[0016] Illustrative embodiments of the invention are described below. The following explanation provides specific details for a thorough understanding of and enabling description for these embodiments. One skilled in the art will understand that the techniques herein may be practiced within the understanding of the common general knowledge and the disclosure herein. In other instances, well-known structures and functions have not been shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.

[0017] Unless the context clearly requires otherwise, throughout the description and the claims, the words "comprise," "comprising," and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is to say, in the sense of "including, but notlimited to." Words using the singular or plural number also include the plural or singular number respectively. Additionally, the words "herein," "above," "below" and words of similar import, when used in this application, shall refer to this application as a whole and not to any portions of this application. When the claims use the word "or" in reference to a list of two or more items, that word covers all the following interpretations of the word: any of the items in the list, all the items in the list and any combination of the items in the list. When the word "each" is used to refer to an element that was previously introduced as being at least one in number, the word "each" does not necessarily imply a plurality of the elements but can also mean a singular element.

[0018] FIG. 1 demonstrates a communication model that a wearable device 100 that could be used for neurofeedback measurements and data transmission through a peripheral nervous system 106. One or more digital signals may be created at a source electrode 101 by the processor 111 and other electronics in a wearable device 100. A transmitter system 102 may emit a carrier signal 103 which may deliver a continuous analog signal along nerve fibers enabling the transmission of white noise 104 and / or data. The combination of white noise 104 with a carrier signal 103 may enable a detection of brain waves by application of stochastic resonance. A modulated signal 105 may travel from where the source electrodes 101 are placed on the skin 205, conducting along nerve fibers (described in more detail below) towards the brain 107. While in transit, the carrier signal 103 that is actively transmitting along a stable pathway between the brain 107 and any area of the peripheral nervous system 106, may cause signal summation between the biological signals and the modulated signal 105. The signal summation may include electrostimulation, background noise, and / or very low frequency brainwaves. The low-frequency brainwaves may be neurological oscillation patterns categorized as one or more of gamma waves, beta waves, alpha waves, theta waves, and delta waves. A receiver system 108 may sample this combination of neurofeedbacksignals 109 which is sent to the sink electrode 110 of the wearable device 100. Although the transmitter system 102, the receiver system 108, and the processor 111 are shown as separate from the wearable device 100, other aspects may have the transmitter system 102, the receiver system 108, and the processor 111 within the wearable device 100.

[0019] Source electrodes 101 may be a conductive metal, a conductive gel, or a combination of the metal and the gel that are placed against the skin 205. The source electrodes 101 may conduct the modulated signal 105 into the epidermis layer 205. Passing through each layer of the skin 205 into the unmyelinated parts of the nerves as illustrated.

[0020] Conventional methods of electroencephalogram (EEG) signal measurement may not be practical for a continuous, convenient method of neurofeedback measurements throughout the day. Current methods employ sensing apparatus that may require EEG electrodes to be placed on a head, such as in headwear, caps, and / or headbands. The EEG electrodes may be prone to noise or spurious signals as motion of the user may cause the EEG electrodes to lose contact with the head and / or shift on the head. The EEG electrodes may be connected to a power supply limiting possible use cases of the product. Aspects herein may eliminate or reduce charging of a separate device by using existing infrastructure, such as smart phones and / or watches. Using the techniques herein may be incorporated into wearable devices, such as necklaces, patches, and / or other devices worn peripherally.

[0021] Turning to FIG. 2, a conceptual overview of a sensory - motor pathway 200 for measuring EEG signals from peripheral nervous system 106 is demonstrated. A sensory stimulation 201 may be experienced as a complex combination of pressure (touch) 202 and / or temperature 203. A skin comprises of an epidermis layer 205, a dermis layer 206, a hypodermis layer 207, and a musclelayer 208. When an electromotive force (EMF) 204 is conducted through the skin 205, the EMF 204 may conduct directly to an axon of a sensory receptor through one or more small gaps between myelinated sheaths. The small gaps may be located along the axons of Merkel disks 209, free nerve endings 210, Meissner’s corpuscles 211, Ruffin’s endings 212, root hair plexus 213, Pacinian corpuscles 214, and / or any other nerves that connects to the peripheral nervous system 106. The EMF 204 may radiate out from a source electrode 101, unless an additional conductor is implemented as a receiver system 108. Any unmyelinated parts of the axon may act as a point of conduction and may be used as a transmission medium which can relay the EMF 204 signal that has been generated externally to the human body. A natural or artificially generated electromagnetic signal may stimulate an unmyelinated gap of an axon within the skin 205.

[0022] Sensory stimulation 201 may be relayed as action potentials along one or more visceral axons 215 and one or more somatic axons 216 where a dorsal root ganglion 218 and a posterior horn 219 pre-processes incoming sensory input for transmission across a vertebrae. Once inside the vertebrae, the sensory stimulation 201 may be further relayed along a spinal cord towards a brainstem 221. The sensory stimulation 201 may pass through a medulla oblongata 222, a pons 224, and a midbrain 226 along a fasciculus cunteatus 223 and one or more lateral spinothalamic tracts 225. The signaling operations that occur in the dorsal root ganglion 218 and brain 107 may operate similar to routing and data processing methods used in computer and networking. In combination with signal modulation, methods such as first-in-first-out and priority queuing may be applied to accurately transmit a modulated signal 105.

[0023] As shown in FIG. 3, one or more modulation methods 301 applied to the sensory stimulation source electrode 101 is shown. A plurality of modulation methods 301 may be stored in a tangible computer-readable medium (not shown) to be executed by a processor 111. Themodulation methods 301 may comprise at least one of: a spread spectrum signal 302, a pulse modulation signal 303, a digital signal 304, and / or an analog signal 305. The pulse modulation signal 303 may be similar to that used in transcutaneous nerve stimulation devices, robotic prosthetics, and / or brain-to-computer interfaces (BCI). The brain 107 operates using analog signals as opposed to digital signals used in computer communication making amplitude 306 and frequency modulation 307 more suitable for signal communication with the brain 107. In some aspects, the input signals may interact directly with the brain.

[0024] Turning to FIG. 4, an electrical representation of a biological system 400 is provided. Each layer of the skin 205 may act as a resistive-capacitive (RC) circuit that filters out portions of the sensory stimulation 201. In this aspect, when a modulated signal 105 is conducted into the skin 205 by the source electrodes 101, the RC circuit 402, 403 respective to each layer 205, 206, 207, 208 undergoes a dielectric breakdown. The dielectric breakdown enables a modulated signal 105 to penetrate through the epidermis layer 205 and conduct into the nerves. Where the signal can conduct and propagate along nerves towards the brain 107.

[0025] An electrical equivalent model 402, 403 for the tissue layers of the skin 205 can be used to calculate one or more parameters for a signal to be transmitted through the skin 205 and along the peripheral nervous system 106 to the brain 107. Mathematically modeling the signal propagation through resistive-capacitive (RC) circuits 402, 403 can provide the parameters for signal transmission through the peripheral nervous system 106.

[0026] A maximum signal transmission can be found by applying Shannon’s theorem to cable theory. The maximum signal transmission may be dependent on a subtype, a degree of myelination, and / or a diameter of the beta fiber 217. A side effect of transmitting the carrier signal103 along the beta fibers 217 at a maximum rate may dull other sensations received by the peripheral nervous system 106 in the surrounding area.

[0027] Turning to FIG 5, the transmitter system 102 and the receiver system 108 are shown in more detail. The transmitter system 102 may comprise a digital-to-analog converter (DAC) 503 that receives a digital signal from the processor 111 to be converted into an analog signal. In this aspect, the DAC 503 may comprise multiple DAC channels. One of the DAC channels may generate white noise 104, another DAC channel may generate a carrier signal 103, and another DAC channel may generate analog data. Each of the DAC channels may be modulated together. In another aspect, the transmitter system 102 may comprise a white noise generator 504 generating the white noise 104, a carrier signal generator 505 generating the carrier signal 103, and a data modulator 506. The modulated signal 105 may be conditioned by a signal conditioning 507, such as filtering and / or amplification. The conditioned signal may then be provided to an emitter 508 to the source electrodes 101. The peripheral nervous system 106 may then process the modulated signal 105 as previously described.

[0028] Digital commands from the processor 111 instruct the generation of the carrier signal 103. This modulated signal 105 is conditioned through a series of filter steps, the emitter 508 may conduct the carrier signal 103 directly through the layers 205, 206, 207, 208 to unmyelinated gaps along the axons of the peripheral nervous system 106. Signals conducted along the peripheral nervous system 106 may form a pathway of signal transduction between the electrode area placement and the brain 107. The carrier signal 103 may travel along this formed pathway and pick up any biological noise.

[0029] Data can be encoded into the carrier signal 103 by mimicking one or more natural patterns of neural activity. Data may be encoded into patterns of electrical stimulation using different frequencies, amplitudes, and / or durations at precise timing. The nature of the brain’s neuroplasticity may result in users decoding data embedded from the modulated signal 105.

[0030] A receiver system 108 receives the combination of the carrier signal 103 and the neurofeedback feedback signal (e.g. biofeedback) and processes this signal through a series of hardware and software steps which includes amplification, filtration, analog to digital conversion, demodulation, and digital signal processing. Particularly, the receiver system 108 may comprise a sensor 510 receiving the neurofeedback signal 109. The neurofeedback signal 109 may be amplified by one or more amplifiers 511 and / or filtered by one or more filters 512. The amplified and / or filtered neuro feedback signal 109 may then be converted to a digital neurofeedback signal using an analog-to-digital converter (ADC) 513. The digital neurofeedback signal may be processed by the processor 111. According to an aspect, the processor 111 may account for a time delay of the modulated signal 105 associated with a propagation of the modulated signal 105 through one or more of: the peripheral nervous system 106, the brain 107, and / or the receiver system 108. The processor 111 may provide no instructions to the DAC 503 during the time delay to reduce interference between the transmitter system 102 and the receiver system 108.

[0031] In some aspects, the transmitter system 102 and the receiver system 108 may each use one or more unshared electrodes 101, 110. In other aspects, the transmitter system 102 and the receiver system 108 may use one or more shared electrodes 101, 110 and the processor 111 may instruct the transmitter system 102 and receiver system 108 to perform time-division duplex use of the shared electrodes 101, 110. In this configuration, time delays between transmitting and receiving are allocated into timeslots. A length of time may be determined by a calibration process and anaccuracy may be reinforced by an algorithmic conditioning over a repeated usage with each user. In addition to time division duplex, other duplexing and multiple access techniques, such as frequency division duplex, time division multiple access, code division duplex, half duplex, echo cancellation, and / or space division duplex may be used to manage the transmission and reception. Calibration of the transmitter system 102 and the receiver system 108 may involve an initial factory calibration which maintains or continuously improves accuracy and reliability through a closed loop feedback system during use.

[0032] This process may generate a continuous stream of neurofeedback data from the neurofeedback signal 109 that is read at by the wearable device 100 (e.g., an input pin on the processor 111) and may be recorded to a computer-readable memory. The neurofeedback signal 109 may comprise gamma waves, beta waves, alpha waves, theta waves, and / or delta waves. The system can process collected brainwave data. Data may be encoded into a carrier signal 103 through an algorithm such that the brain 107 may interpret data while the wearable device both recording and stimulating neural activity.

[0033] The neurofeedback data captured by a wearable device 100 located on the peripheral nervous system 106 can be utilized by applications. These applications may include health care monitoring for physical and mental health and / or software controlled by a brain to computer interface.

[0034] According to an aspect, the source electrodes 101 transmitting the frequency modulated signal 105 to the peripheral nervous system 106 may cause suppression of pain at or near the area of placement (e.g. a painless effect). A lack of pain may be experienced when transmission is maximized through the frequency modulated signal 105.

[0035] According to another aspect, when a frequency modulated signal 105 is transmitted along the peripheral nervous system 106 and to the brain 107, a direct connection may be formed between the brain 107 and area of electrode placement. Subsequently, the modulated signal 105 transmitted through the skin to the peripheral nervous system 106 combines with any biological signals by means of signal summation.

[0036] According to yet another aspect, isolating low frequency waves through signal processing and stochastic resonance may enable neurofeedback oscillations to be recorded from the wearable device 100 placed anywhere the peripheral nervous system 106.

[0037] Once a direct connection is established and neurofeedback is recorded, data can be added into the carrier signal 103 through data modulation of the carrier signal 103. When data, in the form of bits or bytes, are encoded as digital or control data onto a modulated signal 105 and relayed along the carrier signal's pathway to brain 107. The data, expressed in an analog form, can be interpreted by the brain 107.

[0038] The entire system can be designed into a smart watch or other form of wearable technology that is placed anywhere on the peripheral nervous system 106.

[0039] According to an aspect, the process of wearable brain to computer interfacing is a four-part process that comprises the steps of: signal acquisition, data processing, interpretation, and computer execution. The neurofeedback signal 109 may be acquired by the receiver system 108 from the peripheral nervous system 106 and the ADC 513 conversion converts the neurofeedback signal 109 into computer readable data. The processor 111 receiving a continuous stream of neurofeedback data from the neurofeedback signal 109 and preprocesses the neurofeedback data stream through an artifact removal process, a segmentation process, a feature extraction process,and a pattern recognition process. In some aspects, one or more of these preprocesses may be a trained artificial intelligence model and / or a trained machine learning model. A decision process may comprise classifier outputs being compared to one or more predefined thresholds for command execution to occur. Example, when the output of a classifier indicates a high probability of a user intending to click on a button, a command associated with the button may be executed. Execution on a computer in context of neurofeedback involves the terms command, action, and task execution, event handling, or system response. The processor 111 may manage generated commands that may be executed on the physical computer, connected devices or an HTTP request to a website.

[0040] When a full duplex communication system is established between a brain 107 and wearable device 100, such as a smart watch, a user may control a wearable device and / or computer with thought. The user may operate an application layer (e.g. end user) of the OSI (opensource interconnection) model. Through thought, a user operation may execute functions by accessing and / or executing protocols such as TELNET, FTP, TFTP, NFS, SMTP, LPD, IRC & HTTP / HTTPS. The user may read, write, execute, or transfer files, access an intranet, internet or extranet and access / control networked resources. In some aspects, one or more interactions may be interpreted by the processor 111 from a brain through the neurofeedback signal and the interactions may be transmitted over a computer network 150 to another processor (not shown).

[0041] In some aspects, a body area network may be established through the user via the brain-to- computer interface described herein. In other aspects, the body area network may connect to the body area network of other users to exchange neural data to facilitate communication and / or collective computing. Via the connection, the users may interact in a collaborative work environment and / or engage in telepresence through the brain-to-computer interfaces. In anotheraspect, mental health treatments may be performed through a neural-linked group therapy and rehabilitation via the brain-to-computer interface. Similarly, physical diagnosis and / or treatments may be provided by the brain-to-computer interface. In yet another aspect, the users may engage in social entertainment, such as gaming and / or virtual reality facilitated by the brain-to-computer interfaces.

[0042] Applications may involve physical and / or digital security, operational control of computer- based systems, neuro-prosthetics, Brain-Computer-Interface telecommunications, physical or mental neurofeedback rehabilitation.

[0043] A Security Information and Event Management (SIEM) system may be designed to monitor an individual’s location and health. The system would collect data on an individual’ s brain wave patterns when attempting to access a system or area. People entering the areas may check-in by being prompted, then confirming their identity by thought. Real-time analysis could monitor individuals and generate alerts.

[0044] Workers in the field of manufacturing and production use machinery and computers to execute tasks. Machinery such as forklifts, conveyors, lifts, can be operated manually or automated to conduct tasks. The worker at a plant may be able to access one or more machines to execute a variety of tasks through thought through a corporation’s network.

[0045] Neuro-prosthetics may have an external or internal controller to be interfaced with the human body. Through neuromodulation, mechanical limb systems may be controlled by a user to allow control over disabled or missing body parts. The same functionality may be accomplished with a wearable device that communicates with the brain through the peripheral nervous system, controlling prosthetics or damaged areas through the peripheral nervous system. One or moresignals may be sent over EEG bandwidth ranges to allow full-duplex communication between a user’s brain and neuro-prosthetics.

[0046] VOIP (voice over internet protocol) is a method for delivering voice communications over IP (internet protocol) networks. Isolated thoughts contained in the neurofeedback data may be translated by the wearable device which could be relayed to communication networks.

[0047] Physical and mental rehabilitation may be possible through a feedback loop. A doctor would be able to able access data, interpret recordings and administer or adjust treatments as required.

[0048] The above detailed description of the embodiments of the invention is not intended to be exhaustive or to limit the invention to the precise form disclosed above or to the particular field of usage mentioned in this disclosure. While specific embodiments of, and examples for, the invention are described above for illustrative purposes, various equivalent modifications are possible within the scope of the invention, as those skilled in the relevant art will recognize. Also, the teachings of the invention provided herein can be applied to other systems, not necessarily the system described above. The elements and acts of the various embodiments described above can be combined to provide further embodiments.

[0049] All of the above patents and applications and other references, including any that may be listed in accompanying filing papers, are incorporated herein by reference. Aspects of the invention can be modified, if necessary, to employ the systems, functions, and concepts of the various references described above to provide yet further embodiments of the invention.

[0050] Changes can be made to the invention considering the above "Detailed Description." While the above description details certain embodiments of the invention and describes the best mode contemplated, no matter how detailed the above appears in text, the invention can be practiced in many ways. Therefore, implementation details may vary considerably while still being encompassed by the invention disclosed herein. As noted above, particular terminology used when describing certain features or aspects of the invention should not be taken to imply that the terminology is being redefined herein to be restricted to any specific characteristics, features, or aspects of the invention with which that terminology is associated.

[0051] While certain aspects of the invention are presented below in certain claim forms, the inventor contemplates the various aspects of the invention in any number of claim forms.Accordingly, the inventor reserves the right to add additional claims after filing the application to pursue such additional claim forms for other aspects of the invention.

[0052] The foregoing is considered as illustrative only of the principles of the invention. Further, since numerous changes and modifications will readily occur to those skilled in the art, it is not desired to limit the invention to the exact construction and operation shown and described, and accordingly, all such suitable changes or modifications in structure or operation which may be resorted to are intended to fall within the scope of the claimed invention.

Claims

What is claimed is:

1. A method of measuring a neurofeedback signal comprising: generating an input signal; providing the input signal to a peripheral nervous system; allowing the input signal to propagate through the peripheral nervous system; and receiving the neurofeedback signal from the peripheral nervous system.

2. The method according to claim 1, further comprising: modulating a carrier signal with at least one of: white noise or data to modulate the input signal.

3. The method according to claim 2, wherein the modulating is at least one of: a spread spectrum modulation, a pulse modulation, an amplitude modulation, and a frequency modulation.

4. The method according to claim 1, further comprising: recording the neurofeedback signal on a memory.

5. The method according to claim 1, wherein the neurofeedback signal comprises at least one of: gamma waves, beta waves, alpha waves, theta waves, and delta waves.

6. The method according to claim 5, further comprising: processing the neurofeedback signal to determine at least one of: gamma waves, beta waves, alpha waves, theta waves, and delta waves.

7. A system for measuring a neurofeedback signal comprising: a transmitter system coupled to a peripheral nervous system; a receiver system coupled to the peripheral nervous system;a processor configured to execute instructions from a computer-readable memory, the instructions comprising: generating an input signal; providing the input signal to the transmitter system; waiting for the input signal to propagate through the peripheral nervous system; and receiving the neurofeedback signal from the receiver system.

8. The system according to claim 7, wherein the transmitter system comprises a digital-to- analog converter receiving the input signal from the processor and an emitter providing the input signal to the peripheral nervous system.

9. The system according to claim 8, wherein the transmitter system further comprises a white noise generator modulating with the input signal.

10. The system according to claim 8, wherein the transmitter system further comprises a modulator configured to modulate a continuous carrier signal with the input signal.

11. The system according to claim 9, wherein the modulator is configured to perform at least one of: a spread spectrum modulation, a pulse modulation, an amplitude modulation, and a frequency modulation.

12. The system according to claim 7, wherein the input signal suppresses pain at or near a location of the transmitter system.

13. The system according to claim 7, further comprising instructions to: record the neurofeedback signal on the computer-readable memory.

14. The system according to claim 7, wherein the neurofeedback signal comprises at least one of: gamma waves, beta waves, alpha waves, theta waves, and delta waves.

15. The system according to claim 14, further comprising instructions to: process the neurofeedback signal to determine at least one of: gamma waves, beta waves, alpha waves, theta waves, and delta waves.

16. The system according to claim 7, wherein the instructions further comprise: executing at least one computer command in response to the neurofeedback signal.

17. The system according to claim 7, wherein the instructions further comprise: receiving an interaction from a brain through the neurofeedback signal; and transmitting the interaction over at least one of: a computer network, a cloud network, and a body area network.

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