Auditory binaural beats guided by electroencephalography feedback

Abstract

Systems and associated methods for electroencephalography (EEG) biofeedback comprise an EEG signal capturing device comprising at least one electrode, an amplifier, and a transmitter for transmitting an EEG signal, an audio device comprising a first side output and a second side output; and a computer system, configured for receiving an EEG signal from the EEG signal capturing device, identifying a current predominant brain frequency in the EEG signal, causing a base frequency to be played by the audio device, and causing a modified frequency to be played by the first side output of the audio device while the base frequency is played by the second side output of the audio device creating a binaural beat, until the current predominant brain frequency matches the difference between base frequency and the modified frequency.

Description

AUDITORY BINAURAL BEATS GUIDED BY ELECTROENCEPHALOGRAPHYFEEDBACKCROSS REFERENCE TO RELATED PATENT APPLICATIONS

[0001] This application claims the priority and benefit under 35 U.S.C. §119(e) of U.S. Provisional Patent Application Serial No. 63 / 572,772 filed April 1 , 2024, entitled “AUDITORY BINAURAL BEATS GUIDED BY ELECTROENCEPHALOGRAPHY FEEDBACK”. U.S. Provisional Patent Application Serial Number 63 / 572,772 is herein incorporated by reference in its entirety.

[0002] This application claims the priority and benefit under 35 U.S.C. §119(e) of U.S. Provisional Patent Application Serial No. 63 / 747,514 filed January 21 , 2025, entitled “SYSTEMS AND METHODS FOR OPTIMIZATION OF THE BRAIN USING ELECTRODE ELECTROENCEPHALOGRAPHY”. U.S. Provisional Patent Application Serial Number 63 / 747,514 is herein incorporated by reference in its entirety.TECHNICAL FIELD

[0003] Embodiments are generally related to the field of medical devices. Embodiments are also related to the field of biofeedback-based devices. Embodiments are related to audio devices. Embodiments are also related to electroencephalography (EEG) and associated outputs. Embodiments are also related to auditory devices for altering states of consciousness. Embodiments are further related to EEG biofeedback in order to change the state of consciousness of an individual to a desired state using an adapting auditory binaural beat. Embodiments are related to biofeedback. Embodiments are related to input arrangements, or combined input and output arrangements, for interaction between a user and computer. Embodiments are further related to systems, and associated methods, for optimization of the human brain to a target state using auditory binaural beats, direct skull bone vibration and transcranial direct current stimulation (tDCS) guided by continuous EEGfeedback.BACKGROUND

[0004] The proliferation of audio products claiming to facilitate various mental states, such as relaxation, enhanced performance, increased focus, improved sleep quality and mindfulness, is extensive, with thousands of free and commercial offerings available. However, the efficacy of these audio products is often unsubstantiated, lacking in scientific rigor, and not supported by empirical evidence.

[0005] Many existing audio products that claim to offer health benefits do not take into account the dynamic and individualized nature of brain activity which varies, not only from person to person, but also within the same individual under different circumstances. For example, an audio track that purports to induce relaxation may instead trigger adverse effects such as dizziness or headaches in some users. Likewise, the same individual may experience different results under different conditions or times, such as during workdays versus weekends, or after engaging in activities like watching sports. Another often reported limitation of relaxation-based audio products is unintentionally inducing sleep.

[0006] Altering “brain state”, broadly refers to altering the predominant frequency of the brain. Extensive research has been completed to determine if this can be used to improve mental health and well-being, or to optimize human performance. While many studies have supported the proposition that modifying brain frequency may induce desired brain states, other studies have challenged this notion. In particular, brute force approaches where a person is exposed to a given frequency does not guarantee desired results because the brain may not be in a receptive state for the delivered frequency. In some cases, some prior art approaches are even counterproductive, resulting in adverse effects including discomfort and dizziness.

[0007] The landscape of wearable technology has evolved significantly, with a growing emphasis on devices that monitor physiological signals and provide feedback to enhance cognitive and physical well-being. Despite advancements, current devices often operate in silos, focusing on singular functionalities without offering an integrated solution that combinesmonitoring and multi-modal feedback in a compact form factor.

[0008] Wearable monitors are commonly found in fitness trackers, sleep trackers and smartwatches. These devices can monitor heart rate and can detect arrhythmias, contributing to cardiovascular health management. Other monitoring is also developing in consumer wearables used for sleep studies to track eye movements and diagnose disorders like REM sleep behavior disorders. Devices specially designed for this purpose are typically bulky, and not well suited for continuous, everyday use.

[0009] Other monitoring devices targeting neurostimulation to enhance cognitive functions and athletic performance are also being developed. These devices provide electrical currents to specific brain regions to improve neuroplasticity during training. While effective in their domain, these devices do not incorporate physiological monitoring or feedback mechanisms, limiting their adaptability to the user's real-time physiological state.

[0010] Some wearable technologies provide haptic feedback or combine multiple sensory inputs. For example, certain wristbands translate sound into vibrational patterns, aiding individuals with hearing impairments. Similarly, certain meditation applications use audio cues to guide breathing and relaxation. However, these solutions do not integrate physiological data monitoring or advanced stimulation techniques, reducing their potential effectiveness in modulating cognitive states.

[0011] As such, there is a need in the art for adaptive audio systems, and other such monitoring systems that are responsive to the mental state of the user, by employing realtime data collection and feedback mechanisms to tailor an audio output as described herein.SUMMARY

[0012] The following summary is provided to facilitate an understanding of some of the innovative features unique to the embodiments disclosed and is not intended to be a full description. A full appreciation of the various aspects of the embodiments can be gained by taking the entire specification, claims, drawings, and abstract as a whole.

[0013] It is, therefore, one aspect of the disclosed embodiments to provide tailored auditory feedback to alter mental states.

[0014] It is another aspect of the disclosed embodiments to provide methods and systems for altering a state of consciousness.

[0015] It is another aspect of the disclosed embodiments to provide methods and systems for electroencephalographic (EEG) biofeedback in order to change the state of consciousness of an individual to a desired state using an adapting auditory binaural beat.

[0016] It is another aspect of the disclosed embodiments to provide input arrangements, or combined input and output arrangements, for interaction between a user and computer.

[0017] It is another aspect of the disclosed embodiments to provide a wearable device with inputs and outputs located specifically to engage a user’s head at desired locations to achieve desired outcomes.

[0018] It is another aspect of the disclosed embodiments to provide systems, and associated methods, for optimization of the human brain to a target state using auditory binaural beats, skull bone vibration and transcranial direct current stimulation guided by continuous electroencephalography feedback with a wearable device and / or associated computer system.

[0019] Embodiments disclosed herein are directed to a system that leverages audio product design, to generate subliminal binaural beats applied with a stepwise algorithm to ensure the guidance of the predominant frequency of the brain to a desired state (e.g., aspecific frequency within the range of high alpha for relaxation, low alpha to enhance receptivity to suggestions, theta to enhance a meditation experience, etc.). The present invention also provides a user with a measured relaxation experience and provides feedback regarding the initial brain state, success in achieving the target brain state, time taken to achieve the target brain state, time spent in the target brain state and interruptions.

[0020] Embodiments disclosed herein generally comprise an EEG signal capturing and wireless transmitting device, a device that is equipped with a wireless EEG signal receiver, and a binaural audio device. The EEG device provides a signal indicative of the current brain state. The current brain state is used to generate an audio output via the sound adapter, that includes an auditory binaural beat tailored to drive the user to a desired mental state.

[0021] For example, in an embodiment, a system for electroencephalography (EEG) biofeedback comprises an EEG signal capturing device comprising an active recording electrode and a computer system, the computer system further comprising: at least one processor, a user interface, and a computer-usable medium embodying computer program code, the computer-usable medium capable of communicating with the at least one processor, the computer program code comprising instructions executable by the at least one processor and configured for: receiving an EEG signal, identifying a current predominant brain frequency in the EEG signal causing a base frequency to be played in stereo by an audio device comprising a first side output and a second side output, causing a modified frequency to be played by the first side output of the audio device, until the current predominant brain frequency matches a difference between the base frequency and the modified frequency, and causing at least one additional modified frequency to be played by the first side output of the audio device, until the current predominant brain frequency matches a difference between the base frequency and the at least one additional modified frequency. In an embodiment of the system for EEG biofeedback at least one additional frequency comprises a plurality of additional modified frequencies, wherein the instructions executable by the at least one processor is configured for causing each of the plurality of modified frequencies to be played by the first side output of the audio device in series, until the current predominant brain frequency matches a last of the plurality of frequencies perceived by the difference between the frequencies of the first side and second side outputsof the audio device. In an embodiment of the system for EEG biofeedback the last of the plurality of modified frequencies comprises a target brainwave bandwidth. In an embodiment of the system for EEG biofeedback the computer program code comprising instructions executable by the at least one processor is further configured for accepting input indicative of the target brainwave bandwidth. In an embodiment of the system for EEG biofeedback the target brainwave bandwidth comprises one of: Delta waves of 0.1 to 4 Hz, Theta waves of 4 to 8 Hz, Low Alpha waves of 8 to 10 Hz, High Alpha waves of 10 to 14 Hz, Beta waves of 14 to 30 Hz and Gamma waves of 30 to 100 Hz. In an embodiment of the system for EEG biofeedback the instructions executable by the at least one processor is configured for causing the second side output of the audio device to continually play the monotone base frequency wherein the monotone base frequency differs from the modified frequency. In an embodiment of the system for EEG biofeedback the difference between the monotone base frequency and the modified frequency creates a binaural beat. In an embodiment of the system for EEG biofeedback the EEG signal capturing device further comprises a headband, one or more electrodes which may serve as active and reference electrodes, and a ground electrode. In an embodiment of the system for EEG biofeedback the EEG signal capturing device further comprises an amplifier for amplifying the EEG signal and a transmitter for transmitting the EEG signal. In an embodiment of the system for EEG biofeedback the computer program code comprising instructions executable by the at least one processor is further configured for eliminating artifacts in the EEG signal and applying a band pass filter to the EEG signal in order to generate a processed EEG signal. In an embodiment of the system for EEG biofeedback the computer program code comprising instructions executable by the at least one processor is further configured for generating a power spectrum for the processed EEG signal.

[0022] In an embodiment, a computer implemented method for electroencephalography (EEG) biofeedback comprises receiving an EEG signal from an EEG signal capturing device, identifying a current predominant brain frequency in the EEG signal, causing a monotone base frequency to be played in stereo by an audio device comprising a first side output and a second side output, causing a modified frequency to be played by the first side output of the audio device, until the current predominant brain frequency matches a differencebetween the base frequency and the modified frequency, and causing at least one additional modified frequency to be played by the first side output of the audio device, until the current predominant brain frequency matches a difference between the base frequency and the at least one additional modified frequency. In an embodiment of the computer implemented method for EEG biofeedback the at least one additional frequency comprises a plurality of additional modified frequencies, the method further comprising causing each of the plurality of modified frequencies to be played by the first side output of the audio device in series, until the current predominant brain frequency matches a last of the plurality of modified frequencies. In an embodiment of the computer implemented method for EEG biofeedback each of the plurality of modified frequencies comprises a frequency equidistant from its neighboring frequencies in one of an ascending or descending series. In an embodiment of the computer implemented method for EEG biofeedback the last of the plurality of modified frequencies comprises a target brainwave frequency bandwidth. In an embodiment the computer implemented method for EEG biofeedback further comprises causing the second side output of the audio device to continually play the monotone base frequency, wherein the monotone base frequency differs from the modified frequency, wherein the difference between the monotone base frequency and the modified frequency creates a binaural beat. In an embodiment the computer implemented method for EEG biofeedback further comprise eliminating artifacts in the EEG signal and applying a band pass filter to the EEG signal in order to generate a processed EEG signal. In an embodiment the computer implemented method for EEG biofeedback further comprises generating a power spectra for the processed EEG signal.

[0023] In an embodiment a system for EEG biofeedback comprises an EEG signal capturing device comprising an electrode, an amplifier, and a transmitter for transmitting an EEG signal, an audio device comprising a first side output and a second side output, and a computer system, the computer system further comprising: at least one processor, a user interface, and a computer-usable medium embodying computer program code, the computer-usable medium capable of communicating with the at least one processor, the computer program code comprising instructions executable by the at least one processor and configured for: receiving an EEG signal from the EEG signal capturing device, identifyinga current predominant brain frequency in the EEG signal, causing a base frequency to be played by the audio device, and causing a modified frequency to be played by the first side output of the audio device, until the current predominant brain frequency matches a difference between the base frequency and the modified frequency. In an embodiment of the system for EEG biofeedback the difference between the base frequency and the modified frequency creates a binaural beat.

[0024] An aspect of the embodiments can include a wearable device, and associated system, for continuous monitoring and optimization of a user's brain states to enhance experiences such as relaxation, sleep, focus, and sustained attention. Aspects of the embodiments can comprise a plurality of sensors configured to record and locally amplify biological data including EEG, ECG, and EOG. Amplified data can be wirelessly transmitted to a processing device for analysis. Based on the physiological data, aspects of the embodiments can comprise delivery of feedback to the user through one or more modalities which can include audio outputs, direct skull bone vibration, tDCS, and combinations thereof. In certain embodiments, feedback can be adjusted in real-time by a control unit to guide the user's brain state toward a desired condition. The system may employ machine learning algorithms to enhance feedback efficacy over time, providing personalized optimization through stored historical data and adaptive interventions.

[0025] Aspects of the embodiments can further include integration of EEG, EOG I blinking and ECG monitoring, coupled with audio outputs, tDCS, and vibrations into a single compact device in order to provide a comprehensive approach to monitoring and modulating cognitive and physiological states. Aspects can further use a frequency following response. It is an aspect of the disclosed embodiments to provide personalized, real-time adaptive interventions using a multi-modal feedback system which can specifically provide synergistic inputs to the brain to modulate brain activity in both short and long-term.

[0026] In an embodiment, a wearable headset device for biofeedback comprises a wearable head mount, an anode associated with the wearable head mount, at least one cathode associated with the wearable head mount, at least one active electrode associated with the wearable head mount, at least one reference electrode associated with the wearablehead mount, at least one ground electrode associated with the wearable head mount, an output associated with the wearable head mount, and a microcontroller configured to receive input from the at least one active electrode associated with the wearable head mount, at least one reference electrode associated with the wearable head mount, at least one ground electrode associated with the wearable head mount, and generate an output signal to the output associated with the wearable head mount device. In an embodiment, wearable headset device further comprises configuring the at least one active electrode in the wearable head mount to be positioned within a 2.5 cm radius of an Fp1 position or an Fp2 position in a 10-20 electrode system. In an embodiment, the at least one reference electrode in the wearable head mount can be positioned substantially within 2.5 cm of a temporal chain of a 10-20 electrode system, the temporal chain comprising F7, T3, T5 and 01 positions on a left side and F8, T4, T6 and 02 positions on a right side. In an embodiment, the at least one of the anode and the at least one cathode is configured to deliver an electrical vector. In an embodiment, the electrical vector comprises one of a continuous electrical vector and a pulsed electrical vector. In an embodiment, the anode and the at least one cathode are configured to provide an electrical vector substantially between an Fp1 position and nasion in a 10-20 electrode system. In an embodiment, the anode in the wearable head mount can be positioned substantially between an Fp1 position and nasion in a 10-20 electrode system. In an embodiment, the anode in the wearable head mount can be positioned substantially within 2.5 cm of either side of a mid-sagittal plane. In an embodiment, the cathodes in the wearable head mount can be positioned bilaterally with substantial symmetry to each other over a temporal region or an occipital region. In an embodiment, wearable headset device further comprises an amplifier configured to amplify signals collected by the at least one active electrode associated with the wearable head mount, the at least one reference electrode associated with the wearable head mount, or the at least one ground electrode associated with the wearable head mount. In an embodiment, the output further comprises at least one of a binaural audio device and a bitemporal bone vibrator. In an embodiment, the output in the wearable head mount can be positioned substantially over the temporal bone.

[0027] In an embodiment, a wearable headset device for biofeedback comprises an anodeassociated, at least one cathode associated with the wearable head mount, wherein the anode and the at least one cathode are configured to deliver an electrical vector, at least one active electrode, at least one reference electrode, at least one ground electrode, and a microcontroller configured to receive input from the at least one active electrode, at least one reference electrode, and at least one ground electrode, and generate an output signal to an output associated with the wearable head mount device. In an embodiment, the at least one active electrode in the wearable head mount can be positioned within a 2.5 cm radius of an Fp1 position or an Fp2 position in a 10-20 electrode system. In an embodiment, the at least one reference electrode in the wearable head mount can be positioned substantially within 2.5 cm of a temporal chain of a 10-20 electrode system, the temporal chain comprising F7, T3, T5 and 01 positions on a left side and F8, T4, T6 and 02 positions on a right side. In an embodiment, the anode and the at least one cathode are configured to provide an electrical vector directed in the anterior-to-posterior direction along the mid-sagittal plane, originating substantially between an Fp1 position and nasion in a 10-20 electrode system. In an embodiment, the anode in the wearable head mount can be positioned in at least one location comprising a location substantially between an Fp1 position and nasion in a 10-20 electrode system and a location substantially within 2.5 cm of either side of the mid-sagittal plane. In an embodiment, the cathodes in the wearable head mount to be positioned bilaterally with substantial symmetry to each other over at least one of a temporal region and an occipital region. In an embodiment, the wearable headset device for biofeedback further comprises an amplifier configured to amplify signals collected by the at least one active electrode associated with the wearable head mount, the at least one reference electrode associated with the wearable head mount, or the at least one ground electrode associated with the wearable head mount.

[0028] In another embodiment, a wearable headset device for biofeedback comprises a wearable head mount comprising a forehead plate and ear hanger loops, at least one active electrode associated with the wearable head mount, at least one reference electrode associated with the wearable head mount, at least one ground electrode associated with the wearable head mount, an output associated with the wearable head mount device, an anode associated with the wearable head mount, at least one cathode associated with the wearablehead mount, and a microcontroller configured to receive input from the at least one active electrode associated with the wearable head mount, at least one reference electrode associated with the wearable head mount, at least one ground electrode associated with the wearable head mount, and generate an output signal to the output associated with the wearable head mount device.BRIEF DESCRIPTION OF THE FIGURES

[0029] The accompanying figures, in which like reference numerals refer to identical or functionally similar elements throughout the separate views and which are incorporated in and form a part of the specification, further illustrate the embodiments and, together with the detailed description, serve to explain the embodiments disclosed herein.

[0030] FIG. 1 depicts a block diagram of a system for electroencephalography (EEG) biofeedback in order to change the state of consciousness of an individual using an adapting auditory binaural beat, in accordance with the disclosed embodiments;

[0031] FIG. 2 illustrates steps associated with a method for processing EEG data collected for an EEG signal capturing device, in accordance with the disclosed embodiments;

[0032] FIG. 3 illustrates steps associated with a method for EEG biofeedback in order to change the state of consciousness of an individual using an adapting auditory binaural beat, in accordance with the disclosed embodiments;

[0033] FIG. 4A illustrates an exemplary EEG signal capturing device; in accordance with the disclosed embodiments;

[0034] FIG. 4B illustrates exemplary electrode locations of an EEG signal capturing device, in accordance with the disclosed embodiments;

[0035] FIG. 5 illustrates exemplary aspects of a system for EEG biofeedback in order to change the state of consciousness of an individual using an adapting auditory binaural beat, in accordance with the disclosed embodiments;

[0036] FIG. 6A illustrates a front elevation view of an exemplary wearable headset device, in accordance with the disclosed embodiments;

[0037] FIG. 6B illustrates two side elevation views of an exemplary wearable headset device, in accordance with the disclosed embodiments;

[0038] FIG. 7A illustrates a front elevation view of an exemplary wearable headset device with integrated hardware, in accordance with the disclosed embodiments;

[0039] FIG. 7B illustrates two side elevation views of an exemplary wearable headset device with integrated hardware, in accordance with the disclosed embodiments;

[0040] FIG. 8 illustrates a block diagram of a biofeedback system including a wearable headset device and computer system, in accordance with the disclosed embodiments;

[0041] FIG. 9 illustrates a flow chart of steps associated with a method for altering brain states using a biofeedback system, in accordance with the disclosed embodiments;

[0042] FIG. 10 depicts a block diagram of a computer system which is implemented in accordance with the disclosed embodiments;

[0043] FIG. 11 depicts a graphical representation of a network of data-processing devices in which aspects of the present embodiments may be implemented; and

[0044] FIG. 12 depicts a computer software system for directing the operation of the data- processing system depicted in FIG. 10, in accordance with an example embodiment.DETAILED DESCRIPTION

[0045] Embodiments and aspects of the disclosed technology are presented herein. The particular embodiments and configurations discussed in the following non-limiting examples can be varied, and are provided to illustrate one or more embodiments, and are not intended to limit the scope thereof.

[0046] Reference to the accompanying drawings, in which illustrative embodiments are shown are provided herein. The embodiments disclosed can be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the embodiments to those skilled in the art. Like numbers refer to like elements throughout.

[0047] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting. As used herein, the singular forms “a”, “an”, and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises” and / or “comprising,” when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0048] Throughout the specification and claims, terms may have nuanced meanings suggested or implied in context beyond an explicitly stated meaning. Likewise, the phrase “in one embodiment” as used herein does not necessarily refer to the same embodiment and the phrase “in another embodiment” as used herein does not necessarily refer to a different embodiment. It is intended, for example, that claimed subject matter include combinations of example embodiments in whole or in part.

[0049] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art. Itwill be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0050] It is contemplated that any embodiment discussed in this specification can be implemented with respect to any method, kit, reagent, or composition of the invention, and vice versa. Furthermore, compositions of the invention can be used to achieve methods of the invention.

[0051] It will be understood that particular embodiments described herein are shown by way of illustration and not as limitations of the invention. The principal features of this invention can be employed in various embodiments without departing from the scope of the invention. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, numerous equivalents to the specific procedures described herein. Such equivalents are considered to be within the scope of this invention and are covered by the claims.

[0052] The use of the word “a” or “an” when used in conjunction with the term “comprising” in the claims and / or the specification may mean “one,” but it is also consistent with the meaning of “one or more,” “at least one,” and “one or more than one.” The use of the term “or” in the claims is used to mean “and / or” unless explicitly indicated to refer to alternatives only or the alternatives are mutually exclusive, although the disclosure supports a definition that refers to only alternatives and “and / or.” Throughout this application, the term “about” is used to indicate that a value includes the inherent variation of error for the device, the method being employed to determine the value, or the variation that exists among the study subjects.

[0053] As used in this specification and claim(s), the words “comprising” (and any form of comprising, such as “comprise” and “comprises”), “having” (and any form of having, such as “have” and “has”), “including” (and any form of including, such as “includes” and “include”) or “containing” (and any form of containing, such as “contains” and “contain”) are inclusive or open-ended and do not exclude additional, unrecited elements or method steps.

[0054] The term “or combinations thereof” as used herein refers to all permutations and combinations of the listed items preceding the term. For example, “A, B, C, or combinations thereof” is intended to include at least one of: A, B, C, AB, AC, BC, or ABC, and if order is important in a particular context, also BA, CA, CB, CBA, BCA, ACB, BAC, or CAB. Continuing with this example, expressly included are combinations that contain repeats of one or more item or term, such as BB, AAA, AB, BBC, AAABCCCC, CBBAAA, CABABB, and so forth. The skilled artisan will understand that typically there is no limit on the number of items or terms in any combination, unless otherwise apparent from the context.

[0055] All of the compositions and / or methods disclosed and claimed herein can be made and executed without undue experimentation in light of the present disclosure. While the compositions and methods of this invention have been described in terms of preferred embodiments, it will be apparent to those of skill in the art that variations may be applied to the compositions and / or methods and in the steps or in the sequence of steps of the method described herein without departing from the concept, spirit, and scope of the invention. All such similar substitutes and modifications apparent to those skilled in the art are deemed to be within the spirit, scope and concept of the invention as defined by the appended claims.

[0056] Embodiments disclosed herein are generally related to methods and systems for electroencephalography biofeedback in order to change the state of consciousness of an individual to a desired state using an adapting auditory binaural beat.

[0057] Electroencephalography (EEG), as disclosed herein, refers to a technique for recording electrical activity of the brain. This can be achieved through the placement of one or more electrodes on the head or scalp of a participant, allowing for the detection of the brain's spontaneous electrical activity over a period of time. EEG measures voltage fluctuations resulting from ionic current flows within the neurons of the brain.

[0058] In certain disclosed embodiments, single-electrode electroencephalography may be selected because it only requires one electrode placed at a strategic location on the scalp. However, in other embodiments, other electroencephalography devices can also be used. When placed over the pre-frontal cortex, the electrical activity of the brain's frontal lobe iscaptured, which is responsible for high-level cognitive functions and behavior.

[0059] EEG waves can be broadly divided into “bandwidths” known as frequency bands. These are characterized based on their frequency, which is measured in cycles per second (Hz), and include:• Delta waves (0.1 to <4 Hz): Associated with deep sleep and certain pathological conditions;• Theta waves (4 to <8 Hz): Linked to drowsiness, early stages of sleep, and meditation;• Low Alpha waves (8 to <10 Hz): Related to relaxed, calm, and resting states;• High Alpha waves (10 to <14 Hz): Often associated with a state of wakeful relaxation;• Beta waves (14 to 30 Hz): Associated with arousal, active, busy, active thought, concentration, highly complex thought, and can also indicate anxiety; and• Gamma waves (30 to 100 Hz): Associated with enhanced attention, memory encoding, memory retrieval, creativity and problem solving abilities.

[0060] While the brain produces all of these wave types simultaneously, typically one frequency band is dominant at any given time, reflecting the predominant brain state. For instance, during deep sleep, delta waves predominate, while during active concentration, beta waves are more prominent.

[0061] Altering the “brain state”, as disclosed herein, broadly refers to altering the predominant frequency of electroencephalographic activity of the brain. Aspects of the disclosed embodiments include allowing a user to select a desired “brain state”, and then applying an auditory input to guide the brain into a bandwidth associated with that brain state.

[0062] In the disclosed embodiments, auditory binaural beats are leveraged to alter brain state. This can comprise an auditory illusion perceived when two different pure-tone sine waves, both with frequencies lower than 1000 Hz and with less than a 30 Hz difference between them, are presented to a listener dichotically (one through each ear). The brain integrates the two signals, producing a sensation of a third sound called the "beat," whose frequency is equal to the difference between the two frequencies. Effective range for thegeneration of binaural beats falls between 200 Hz and 900 Hz, with optimal detection around 500 Hz.

[0063] Biologically, binaural beats are thought to originate in the superior olivary nucleus of the brainstem. This nucleus, which plays a crucial role in the auditory pathway, is the first site of the binaural interaction in the auditory system where the signals from each ear converge. Neurons within this nucleus are adept at detecting phase differences between sounds heard in each ear, a skill crucial for locating the direction of sounds. When two tones close in frequency generate a phase difference, the superior olivary nucleus interprets it as a beat frequency, thus producing the perception of a binaural beat.

[0064] For purposes of illustration, the following is an example of the computation of binaural frequencies. Consider an individual presented with a tone of 500 Hz in one ear and 510 Hz in the other ear. The superior olivary nucleus computes the difference between these two frequencies, resulting in a perceived binaural beat at 10 Hz. This 10 Hz frequency falls within the alpha range of brainwave activity, often associated with relaxed, awake states.

[0065] Another aspect of the disclosed embodiments is the use of the Frequency-Following Response (FFR), which is a neurophysiological mechanism where brain electroencephalographic activity synchronizes with auditory frequency stimuli. This synchronization is particularly evident with binaural beats. The methods and systems disclosed herein take advantage of the FFR using binaural beats to guide the brain into a bandwidth associated with the desired brain state.

[0066] The disclosed methods and systems can be used for improving mental health and well-being as well as optimization of human performance. For example, the disclosed methods and systems can be used to shift the predominant EEG activity from a faster beta state to low alpha or theta states while maintaining awareness to stimuli (e.g., meditation, hypnotherapy), although it should be appreciated that the methods can also be applied to improve focus or stimulate activity. In certain embodiments, this can help optimize relaxation experiences. In other embodiments, it can be used to introduce and / or alter behavior (e.g., calorie restriction, boost confidence, smoking cessation), improve learning and memory, optimize performance in sports and / or performance arts (e.g., visuo-mental rehearsal), etc.

[0067] Thus, in an embodiment, the disclosed system can comprise an EEG signal capturing device with an associated amplifier and a signal transmitter. The EEG signal capturing device can provide input to a device (such as a computer) that is equipped with an EEG signal receiver, random access memory, and internal storage with associated software modules, a network adapter, a processor, and a sound-adapter. The device can communicate with the EEG device and will execute software modules as further detailed herein. The software modules are configured for receiving and processing the EEG signals (and / or other feedback) to determine the current brain state. The current brain state is then used to execute audio output via a sound adapter and binaural audio device (e.g., headphones or earphones) with a first output side and a second output side.

[0068] For example, the system can generate subliminal binaural beats using a stepwise method to ensure the guidance of the predominant frequency of the brain to a desired state (e.g., high alpha for relaxation, low alpha to enhance receptivity to suggestions, theta to enhance a meditation experience). The embodiments thus provide the user with a measured relaxation experience and provide feedback regarding the initial brain state, success in achieving the target brain state, time taken to achieve the target brain state, time spent in the target brain state and interruptions. In certain embodiments, the system can further comprise a server used to store the EEG signal in both raw and processed form.

[0069] FIG. 1 illustrates a block diagram of a system 100 for electroencephalography (EEG) biofeedback in order to change the state of consciousness of an individual to a desired state using an adapting auditory binaural beat in accordance with the disclosed embodiments.

[0070] The system 100 can include an EEG signal capturing device 105. The EEG signal capturing device 105 can comprise a wearable device with electrodes 1 10. The electrodes 1 10 can include at least one active recording electrode (or active EEG electrode) which can preferably be placed on a user’s head or scalp, a reference electrode, and a ground electrode.

[0071] The EEG signal capturing device 105 can comprise a lightweight device which canbe powered with an on-board battery 115. The battery 115, can be selected to be lightweight, and is configured to power an in-built (or on-board) amplifier 120 and a transmitter 1 5, which can comprise a signal transmitter, which is configured for transmitting amplified raw EEG data to a device 130.

[0072] The device 130 can comprise a data processing system such as a computer, as further detailed herein, that is configured to process the EEG data. The device 130 can include a processor 135 with random access memory 175, internal storage 140, a receiver 145 which can comprise a wireless receiver (and / or wired receiver), a network adapter 150, and a sound adapter 155. It should be appreciated that the device 130 can comprise any of various computing devices such as desktop computers, laptop computers, tablets, smartphones, smartwatches, or other such portable electronics.

[0073] The EEG data can be received by the receiver 145, and processed using the device 130. Aspects of such processing include receiving the EEG signals, determining the current brain state, and executing audio output via the sound adapter 155. The sound adapter 155 can provide input to an audio device 160, which can comprise headphones, earbuds, speakers, earphones, bone vibration devices, or other such audio output devices that are capable of playing sounds in stereo via a first output side and a second output side (most commonly embodied as the two earpieces in a pair of headphones. The audio device 160 can output a subliminal binaural beat, which can optionally be overlaid with an audio track. The subliminal binaural beat provided by the audio output can be altered based on the current brain state as further detailed herein.

[0074] In addition, the system 100 can communicate with a server 165, which can comprise a distant cloud-based server via the network adapter 150. The server 165 can provide instructions and for storage of the EEG signals in both raw and processed form on a storage device 170.

[0075] The embodiments include related processes associated with the collection of brain wave data and generation of binaural beats. FIG. 2 illustrates steps associated with a method 200 for EEG signal processing, in accordance with the disclosed embodiments.

[0076] At step 205 EEG data indicative of current brain activity embodied as brain waves, can be acquired from the EEG signal capturing device 105 (e.g., an EEG headset). The EEG signal can be amplified in its raw form at step 210. In certain embodiments amplification can be completed with an on-board amplifier 120, although it is possible for the signal to be amplified by device 130.

[0077] After amplification, at step 215, the amplified signal can be transmitted via transmitter 125, as packets in real-time (or near real-time). In exemplary embodiments, the packets are transmitted via wireless transmission (e.g., Bluetooth, WiFi, cellular network, etc.) to the processing device 130 that has a wireless data receiver 145.

[0078] At step 220, the processing device 130 can timestamp the received EEG data packets and reconstruct the raw EEG wave based on the order of receipt and the sampling rate of the EEG device.

[0079] Upon reconstruction of the signal, the raw EEG signal can be subject to artifact elimination at step 225. Artifact elimination is necessary because raw EEG signals are noisy. For example, artifact elimination at step 225 can include blink detection and removal. At step 230 band-pass filtering, which can include high-pass and low-pass filtering is completed. Band pass filtering can minimize cardiac, respiratory, muscle artifacts, and other such noise in the signal.

[0080] The processed or conditioned EEG signal can next be used to compute an EEG power spectrum at step 235, so that the predominant current brain wave frequency can be identified.

[0081] The method 200 can be repeated at a regular interval (e.g., once every second, once every five seconds, once every thirty seconds, once a minute, etc.), resulting in a processed predominant EEG frequency derived from the raw EEG signal provided by the EEG device at the desired interval.

[0082] The processed output can be used as a part of the method for generating an audio output to guide a user to a desired mental state as illustrated by method 300 in FIG. 3.

[0083] A session can begin by specifying a desired state and / or brain frequency, as well as a base frequency (qO). A typical (likely unsophisticated) user may not immediately know the desired brain frequency, so defaults can be provided. Over time, the desirable brain frequency may be identified through use. In some embodiments, these options can be presented on a graphical user interface of a device 130, associated with software, as further detailed herein.

[0084] At step 305 background audio can be specified. In certain embodiments, the user can select audio to be played at the baseline. This can be selected from an audio library available locally on a processing device 130, or from a distant cloud-based storage, such as Spotify® or Pandora®. The audio to be played when the brain achieves the target state can also be selected. This audio can be selected from an audio library locally, or from a distant cloud-based storage (e.g., audio containing specific suggestions I affirmations). In certain embodiments, these options can be presented on a graphical user interface, associated with the software.

[0085] At step 310, the sound adapter 155 can cause background audio to be played through audio device 160 (e.g., headphones) along with the monotone base frequency played binaurally (in both the first side output and the second side output) at a sound intensity below a threshold of active awareness for the user, at the base frequency. The monotone base frequency can be identified as qo, and can optionally be selectable. The monotone base frequency can be played to both ears.

[0086] At step 315, EEG data can be acquired with an EEG signal capturing device 105. It should be appreciated that the data acquisition can be done continuously or at a preset interval. In some embodiments, data acquisition can be set for a specified duration of time (e.g., 1 minute) and transmitted to the processing device 130. As illustrated in method 200, EEG signal processing is used to determine the predominant EEG frequency at a baseline (f), and thereafter as the binaural beat is played.

[0087] After the baseline frequency has been determined, at step 320, the frequency played in one side (e.g., one earphone) of the audio device 160 (e.g., the right earphoneproviding sound to the user’s right ear) will be changed by a frequency (f), so that the monotonous frequency played in the one earphone, rji will be the sum of qo + f.

[0088] At step 325, the audio can be played until the baseline frequency, measured by the EEG signal capturing device 105, stabilizes at the previously measured predominant frequency, (f.) This may take only a few seconds, or may take up to several minutes or more. In this context, it is important to note that the predominate frequency of a person’s brain may change rapidly during normal activities. As such, at step 325, it is preferrable to continue to play the audio until the baseline frequency stabilizes at the previously measured predominant frequency (f) for several consecutive minutes. In certain embodiments, an upper and lower variability threshold (e.g., one standard deviation) can be set to determine if the baseline frequency is “stable”. If the baseline frequency exceeds the upper or lower variability threshold, the time resets, and the audio continues to play until the measured frequency (measured using the method 200) stays within the upper and lower variability threshold for an established length of time.

[0089] Once the stabilization of the baseline frequency and coherence with the binaural beats has been confirmed, at step 330 the frequency played in one of the earphones can be changed according to a stepping function by a set amount, for example, a 1 Hz increment I decrement (although other increments / decrements are possible). At step 335, the predominant brain frequency is allowed to stabilize and synchronize with the new binaural frequency of f±1 .

[0090] Once stability and synchronicity has been achieved, at step 340 the frequency played in one side of the audio device 160 is again changed (e.g., further by 1 Hz in the same positive or negative direction as the first step). At step 345, the cycle can be repeated until the frequency played in one of the earphones is f-n from the frequency played in the other earphone, where n is the target frequency, and the predominant frequency of the brain (as detected by method 200) reaches the target frequency for the desired brain state. Once the target frequency has been achieved, the audio may be switched to a desired audio (e.g., affirmations, suggestions, etc.).

[0091] FIG. 4A illustrate an exemplary EEG signal capturing device 105, in accordancewith the disclosed embodiments. As illustrated, the EEG signal capturing device 105 can fit on the head 405 of a user. In certain embodiments, the EEG signal capturing device 105 can include at least one active recording electrode 1 10, with a headband 410, configured to hold the device on the user’s head. FIG. 4A further illustrates an additional ground electrode 415 and reference electrode 420.

[0092] FIG. 4B illustrates exemplary placement of the various electrodes associated with an EEG signal capturing device 105, on a human head 405. As illustrated, the active recording electrode 110 is located proximate to the frontal lobe 450, shown as FP1. The reference electrode 420 is placed on the one side of the head 405. The ground electrode 415 can be placed on the opposite side of the head 405, and slightly higher, such that it is roughly situated at the same elevation on the head 405 as the active recording electrode 1 10.

[0093] FIG. 5 illustrates an exemplary arrangement of components in a system 100 for changing the state of consciousness of an individual to a desired state using an adapting auditory binaural beat in accordance with the disclosed embodiments.

[0094] In this example, the EEG signal capturing device 105 is powered with a battery 1 15 and is equipped with a wireless transmitter 125 paired to a processing device 130 (e.g., a mobile phone) which can be equipped with a wireless signal receiver, processor, memory, internal storage, audio adapters and a network adapter, as illustrated in FIG. 1 .

[0095] The signal collected by the EEG signal capturing device 105 is provided to the processing device 130 as illustrated by line 505. As shown in the method 200 of FIG. 2, the processing device 130 can generate an EEG power spectrum, so that the predominant brain wave frequency can be identified. In FIG. 5, the EEG power spectra of a processed singleelectrode EEG signal plotted against time (1 second) is shown in chart 510. In addition, chart 515 shows the processed EEG signal after being decomposed into frequency bands.

[0096] The processing device 130 can then use the measured brain wave frequency to generate binaural beats as described in method 300, to the audio device 160, as illustrated by line 520. In such embodiments, a base frequency qo, is initially played in both ears. Then, a modified frequency qi is played only in one ear, so that the difference between qo - qimatches the predominant brain frequency (f). Thereafter, the frequency presented in the ear where the modified frequency is being played, can be modified further (qx) in incrementing or decrementing steps, to change the binaural beat frequency (qo - Qx) in order to guide the predominant frequency of the brain to a target state.

[0097] Aspects of the disclosed embodiments are further related to a wearable device, and associated system, for continuous monitoring and optimization of a user's brain states to enhance experiences such as relaxation, sleep, focus, and sustained attention. Such embodiments can include more complex arrangements of sensors and feedback devices to provide better results.

[0098] Certain embodiments can comprise a plurality of sensors configured to record, and locally amplify, biological data including Electroencephalogram (EEG) data, electrocardiogram (ECG) data, and / or Electrooculography (EOG) data. The amplified data can be transmitted to a processing device for analysis. The physiological data is used to deliver feedback to the user through one or more modalities, which can include audio outputs, direct skull bone vibration, tDCS, or combinations thereof. The feedback is adjusted in realtime by a control unit (or microcontroller) to guide the user's brain state toward a desired condition as illustrated in FIGs. 2, 3, and 5.

[0099] Embodiments disclosed herein make use of the potential difference recorded between a pair of electrodes (referred to herein as the active and reference electrodes respectively) which give rise to an electrophysiological signal. The electrophysiological signal recorded over the scalp comprises electrical activity coming from many sources including the surface of the brain (i.e., EEG activity), heart (i.e., ECG activity), changes in position of cornea and retina of the eyes (i.e., EOG activity) as well as overlying muscle activity (i.e., electromyography; EMG activity). The in-built bio amplifier can non-selectively track potential difference between the active electrode and the reference electrode and can transfer the signal to an on-board micro-controller which can transmit data to a processing device.

[0100] The processing device can then provide various functions. For example, the processing device can provide band-pass filtering to ensure isolation of the desired signal,such as EEG activity in ranges from 0.05-200 Hz per Nyquist criterion to capture up to 100 Hz. For ECG a bandpass filter of 0.05-150 Hz can be applied. And for EOG filtering can be in the 0.5-100 Hz range, per Nyquist criterion, to capture up to 50 Hz. The processing device can also provide notch filtering (which can be set at 60 Hz in the US and / or 50 Hz in Europe for example), to account for the AC current’s frequency. The processing device can also provide artifact elimination algorithms and thresholding.

[0101] In the signal processing pipeline, artifact elimination algorithms can be used for blink detection, calculation of entropy, and thresholding based on entropy. Independent component analysis can be used to filter out the purified raw signal for processing.

[0102] The processed signal can be used to make inferences about the brain state. For example, the EEG signal can be fast Fourier transformed with the output used to determine the current predominant frequency band and frequency of the brain. The difference between R-R intervals of ECG signal can be used to compute heartrate variability which is used as a surrogate to predict stages of sleep, emotional state, etc. The EOG signal provides direct inferences about eye movements, and therefore provides data on where a user is looking in a two-dimensional visual field, and can provide data on drowsiness and sleep.

[0103] Embodiments may include machine learning processes used to enhance feedback efficacy over time, providing personalized optimization through stored historical data and adaptive interventions. In certain embodiments, EEG data and demographic data collected from users can be used to fit statistical models, including regression models as well as machine learning models, utilizing superficial and deep learning algorithms. Individual (e.g. demographics, occupation), temporal (e.g. time of the day), interventional (e.g. baseline audio frequencies and background sound tracks used) and situational (e.g. starting frequency and variability of frequency) data influencing the speed of reaching the target brain state, variability of the brain state (e.g. standard deviation of a frequency within the given time epoch), and maintaining the brain activity at the target brain state, will be identified for specific demographics. These results can be used to optimize the delivery of interventions at an individual and / or group level during subsequent iterations. The use of EEG data for this purpose is noteworthy.

[0104] FIG. 6A provides a front elevation view of a wearable headset device 600, and its relative position on a user 650, in accordance with the disclosed embodiments. A plurality of sensors and / or electrodes can be embedded in the headset such that the sensors / electrodes make close contact with the skin 652 of the user 650. The wearable headset device 600 can comprise a head mounted device with a curved forehead plate 602 affixed (or molded to) side struts 604. The side struts 604 are connected to ear hanger loops 606 configured to loop around the ears 658 of the user 650. The curved forehead plate 602 can also include a nose extension 608 configured to extend along the nose 654 to a position between the wearer’s eyes 656.

[0105] FIG. 6B provides profile or side elevation views of the wearable headset device 600 as it is worn by a user 650, in accordance with the disclosed embodiments. As illustrated in this view, the side struts 604 serve as the connection between the curved forehead plate 602 and ear hanger loops 606.

[0106] The wearable headset device 600 is configured to provide contact between sensors / electrodes embedded therein, and the wearer’s skin 652. Embodiments are designed with the aim of continuous monitoring and optimization of a user's brain states to enhance experiences such as relaxation, sleep, focus, and sustained attention. To that end, the wearable headset device 600 is meant to be comfortable to wear for extended periods of time.

[0107] FIG. 7A illustrate the wearable headset device 600 with associated embedded hardware, in accordance with the disclosed embodiments. It should be appreciated that components of the electronic hardware depicted herein may be embodied as compact circuit boards, chips, electrodes, sensors, speakers, haptic feedback devices, or other such electronic components.

[0108] In an embodiment, the wearable headset device 600 can include a set of electrodes. The electrodes can comprise active electrodes 702, reference electrodes 704, and a ground electrode 706 (shown in FIG. 7B). The active electrodes 702 are positioned on the curved forehead plate 602 above the respective eyebrows and, nominally in line with theinner corner of the eye. The reference electrodes 704 are positioned on the ear hanger loops 606 so that they are positioned on the wearers head along the profile of the top of the respective ears 658.

[0109] Electrode and / or sensor positioning is an aspect of the disclosed embodiments. In order to reference certain locations on the head, the 10-20 system notation is used. FIG. 4B provides a reference chart 407 illustrating a diagram of the 10-20 system locations, in accordance with the disclosed embodiments.

[0110] In certain embodiments, the active electrodes 702 can comprise Ag / AgCI coated dry electrodes for EEG I EOG and ECG data recording placed nominally within a radius of 2.5 cm from the Fp1 and Fp2 positions in the 10-20 electrode system. The anode 714 can comprise a tDCS anode, which can also be an Ag / AgCI coated dry electrode. The anode 714 can be positioned nominally over the mid-sagittal plane or within 2.5 cm from the mid-sagittal plane to either side, between nasion and in the Fp position. The reference electrodes 704 can comprise Ag / AgCI coated dry electrodes for EEG / EOG and EKG data recording positioned nominally along the temporal chains of the 10-20 system comprised of the F7, T3, T5 and 01 positions on the left side and F8, T4, T6 and 02 positions on the right side or within 2.5 cm distance from the above chains in the 10-20 electrode system. The cathodes 720 can comprise tDCS cathodes, which can comprise Ag / AgCI coated dry electrodes placed over bilateral mastoids. It should be appreciated that the location of the tDCS cathodes is meant to be exemplary. As long as the cathodes are placed nominally symmetrically bilaterally in temporal or occipital regions of the midline in the occipital region (e.g. within 2.5 cm), a current can be driven along a vector that runs in the mid-sagittal plane in the anterior- posterior direction as required for the disclosed embodiments to function. The ground electrode 706 can comprise Ag / AgCI coated dry electrode. The location of the ground electrode 706 can be placed in other locations as well, including but not limited to, the face, neck, or clipped to the ears. The anode and cathode(s) can be used to deliver transcranial direct current stimulation.

[0111] For example, the anode and cathodes associated with the wearable headset device for biofeedback are configured to deliver a continuous or pulsed electrical vector, startingsubstantially between the Fp1 position and nasion in the 10-20 electrode system and directed in the anterior to posterior direction, or in proximity to the mid-sagittal plane.

[0112] Embodiments are configured for delivery of a current that starts from the front of the head and travels backwards through the head in the midline. The anode placement is key for this purpose. The cathode can comprise a single electrode placed in the back of the head, upper neck, or in the midline. In other embodiments the cathode can be configured as symmetric electrodes placed on either side (e.g. both mastoids) that direct the vector of the current to run in the midline.

[0113] The device 600 can include an output 716. The output 716 can comprise binaural audio devices and / or binaural bone vibrators which, in an embodiment of the current intervention, may be placed over the pre-auricular temporal bone or other bony prominences of the skull symmetrically to provide binaural audio inputs. The output devices associated with the wearable head mount device can comprise binaural audio devices, bitemporal bone vibrators, and electrodes configured to deliver transcutaneous direct current stimulation along the anterior-posterior direction of the head in the mid-sagittal plane.

[0114] A power and data port 724 (shown in FIG. 7A) is included and can be positioned centrally, at the top of the curved forehead plate 602. It should be appreciated that the power and data port 724 can be located in other positions in other embodiments. The set of electrodes are configured to capture EEG, EOG and / or ECG signals. For example, in certain embodiments, the same electrodes can be used to capture multiple signals by varying the thresholding and processing. For instance, the potential difference between active electrodes 702 and reference electrodes 704 on each side, provide data indicative of the difference in the brain’s electrical activity between the frontal and temporal regions (e.g., on the left side of the brain, this would correspond to the Fp1 -T7 channel on an EEG). Also, based on location, the electrodes can provide data indicative of eye movement (e.g., EOG).

[0115] The wearable headset device 600 can further include an inbuilt bio amplifier 708 that amplifies the EEG, EOG and EKG signals collected by the electrodes. In certain embodiments, the inbuilt bio amplifier 708 is integrated in the wearable headset device 600,along the curved forehead plate 602.

[0116] The wearable headset device 600 can include one or more inbuilt micro-controller devices 710 (shown in FIG. 7A). The inbuilt micro-controller devices 710 can have (i.e., Bluetooth and I or WIFI) transmitters, and provide sufficient computational power and memory to implement basic processing of the signals received from the bio-amplifier 708. As further detailed herein the active electrode 702, reference electrode 704, and ground electrode 706 are used to collect signals. The signals can be processed to capture EEG, ECG, and / or EOG activity.

[0117] The wearable headset device 600 can further include an inbuilt wireless signal receiver 814 (shown in FIG. 8), an audio amplifier 712, and an inbuilt direct current buffer 816 (shown in FIG. 8), as further illustrated in FIG. 7A. The buffer is configured to prevent an unnecessary overloading of the micro-controller devices 710 and to prevent it from malfunctioning due to an excessive capacitive load. The wearable headset device 600 can further include an inbuilt output 716 comprising a binaural audio device and / or binaural bone vibrator technology.

[0118] In certain embodiments, the wearable headset device 600 can interact with an external wireless device that is equipped with a wireless signal receiver I transmitter, a processor, random access memory, and internal storage, with stored software instructions, a network adapter, and a sound-adapter. Details of these aspects are further provided herein.

[0119] FIG. 7B provides profile or side elevation views of the wearable headset device 600 as it is worn by a user 650, with various integrated hardware, in accordance with the disclosed embodiments. The wearable headset device 600 can include an output 716 comprising an inbuilt binaural audio device and / or binaural bone vibrator technology. The binaural bone vibrator output 716 can be configured on the ear hanger loop tab 718, which can extend in front of the of the user 650.

[0120] In certain embodiments, a plurality of electrodes are in close contact with skin 652 (i.e., anode 714 placed frontally in or close proximity to the mid-sagittal plane and cathodes 720 placed behind the ear 656), and are capable of delivering tDCS. The wearable headsetdevice 600, can also include batteries 722, used to power the associated hardware. The hardware, sensors, and electrodes can be integrated into the wearable headset device 600 or otherwise associated with the wearable headset device 600 provided they are properly positioned to contact the user at the desired positions.

[0121] FIG. 8 provides a block diagram of certain elements of a system 800 in accordance with the disclosed embodiments. The system 800 can include three main components: a wearable headset device 600, an external (potentially proximal) electronic device 802, which can comprise a mobile phone, tablet, iPad, laptop, or desktop computer, or the like, and a distant cloud-based server 804 equipped with storage.

[0122] The wearable headset device 600 can include reference electrodes 704, active electrodes 702, and the ground electrode 706. The associated signals received from these electrodes are used to process the EEG, ECG, and EOG data by comparing the potential of one as compared to the other. The ground electrode 706 helps to stabilize the baseline and reduce background noise (electrical inference) by subtracting its potential from the signal other two electrodes. The system 800 can further include a bio-amplifier 708 configured to accept input from the electrodes.

[0123] A microcontroller 710 can be provided as a part of the system 800 integrated in the wearable headset device 600. The microcontroller 710 can include a processor 808 with associated random access memory 810. An associated wireless (e.g. Bluetooth and / or WIFI) transmitter 812 and receiver 814 are provided as aspects of the microcontroller 710. A direct current buffer 816 is incorporated in the microcontroller 710.

[0124] The microcontroller 710 can include a power and charging port 724 which can comprise, for example, a LISB-C port for charging and software upgrades. The microcontroller 710 can include an audio amplifier 806, which can comprise stand-alone hardware, or inbuilt in the microcontroller.

[0125] The output 716 that may be an audio speaker and / or binaural bone vibrators, are configured to be placed over the pre-auricular temporal bone.

[0126] The proximal, external electronic device 802 can comprise a mobile phone, tablet, iPad, laptop or desktop computer. The external electronic device 802 can include a wireless receiver 818 and wireless transmitter 820, in operable communication with a processor 822, an internal random-access memory 824, and internal storage 826. The external electronic device 802 can further include a sound adapter 828 and a network adapter 830.

[0127] In certain embodiments, the external electronic device 802 can comprise a phone application or a desktop application that acts as a user interface (Ul). The electronic device 802 can be used to ensure connectivity to the headset and the distant server, ensure continuous receipt of data, and enable the user to designate what they would like to do with the headset. In certain embodiments, the external electronic device can also be used as a loudspeaker to play audio transmitted from the device. In addition, the external electronic device 802 can make use of the sensors built into the headset for recording I monitoring purposes such as sleep tracking (duration of total sleep and different stages of sleep), tracking duration of focused meditation, and can record gaze behavior. In addition, the Ul associated with the external electronic device can be used to specify the intervention the user would prefer (e.g. binaural audio, tDCS, bone vibration, or combinations of the above) with electrophysiological guidance. The Ul can also be used to review a summary of stats from past sessions, and schedule and track progress.

[0128] The distant server 804 can comprise a cloud-based server, which can include a distant processor 832 with memory and distant storage 834. The distant server 804 is configured for pre-processing electrophysiological signals (e.g. EEG), analyzing the EEG data (in real-time, or near real-time), transmitting audio, bone vibration and tDCS outputs to the device 802 and through that to the headset. The distant server 804 is also used for storage of data for retrieval by user (e.g. summaries) or for developing training models and / or further analysis.

[0129] A critical aspect of the disclosed embodiments relates to the tDCS electrode placement on the anatomy of the user. The wearable headset device 600 can be configured so that the disclosed electrodes are located in specific places, in order to realize the desired results.

[0130] In an embodiment, the Anode (+) 714 is configured in the wearable headset device 600 so that it is placed in the mid-sagittal plane just superior to the nasion below the Fp position. The Cathode (-) 220 can comprise a combined electrode placed on bilateral mastoid processes (A1 and A2 in the 10-20 system). This electrode placement is selected based on an observed efficacy in altering EEG activity. Electrophysiologically, the cornea of the eye is positively charged, and the tip of the tongue is negatively charged. Thus, the electrode placement is selected to induce a direct electric current in the mid-sagittal plane between the Fp-nasion region and the base of the brain. This specific electrode placement method for tDCS is unique and can provide the benefits as described herein, in addition to the benefits of the frequency following response.

[0131] FIG. 9 illustrates a method 900 for altering brain states in accordance with the disclosed embodiments. The method begins at step 902. It should be appreciated that the associated steps can be completed in rapid succession in a biofeedback loop.

[0132] At step 904, data is acquired by the various electrodes disposed in or on the wearable headset device 600. In an embodiment, the data acquisition can comprise EEG data, EOG and blinking data, and / or ECG data acquired with the electrodes.

[0133] Next at step 906, the inbuilt amplifier 708 performs onboard amplification of the input signals, and the microcontroller device 710 timestamps and digitizes the signal. The amplified and digitized signal is then transmitted to the external electronic device 802 and / or the distant server 804 as packets, preferably with wireless transmission (although other transmission options, such as wired transmission, are possible) at step 908.

[0134] The packets can be compiled to reconstruct the raw signal as illustrated at step 910. At step 912 signal conditioning of the signal is provided. The signal conditioning can comprise band pass filtering, notch filtering, and / or artifact elimination. The signal is now ready for analysis.

[0135] At step 914 the conditioned signal is processed to determine the current brain and / or physiological state. Once the brain and / or physiological state are determined, in orderto guide the brain or physiological state of a user to a pre-determined target state, a stimulating frequency will be determined at step 916. At step 918, the determined stimulating frequency will be transmitted back to the headset.

[0136] At step 920 a frequency following response is provided. The frequency following response at step 920 can include delivery of the stimulating frequency determined in step 916 using any combination of the modalities including binaural audio, tDCS, or bone vibration based on user preference, which will result in a frequency following response, moving the current predominant brain state towards the predetermined target brain state.

[0137] The method 900 returns to step 904 and iterates until the desired brain and / or physiological state is reached, at which point the method 900 ends at 922.

[0138] Aspects of the disclosed embodiments have been tested for efficacy. Exemplary results of such testing are presented herein. In an exemplary case, tests were conducted to compare the effects of exposure to a 30-minute EEG-guided binaural-beat audio intervention, according to methods and systems disclosed herein, on objective neurophysiological measures of relaxation, sustained attention, inhibitory control, novel memory encoding and retrieval as well as self-reported relaxation and cognitive performance among healthy adults in a randomized, double-blinded, sham-controlled, repeated measures crossover clinical trial.

[0139] This study involved twenty-five healthy adults. The study involved three visits. During the first visit, participants were screened for eligibility, provided informed written consent, received training on the cognitive tasks to be performed and the intervention and sham-control conditions were randomly assigned to the second and third visits. The second and third visits were scheduled at least one day, and no more than one week, apart. At the beginning of each intervention visit, participants completed pre-intervention visual analogue scales (VAS) and cognitive tasks. Next, they underwent either the intervention or sham control condition, randomized and counterbalanced across the second and third visits. Following the 30-minute session, participants again completed the VAS and cognitive tasks. Both participants and researchers administering the tasks were blinded to conditionassignment.

[0140] Aspects of the disclosed systems were used for testing. An EEG electrode was positioned at the Fp1 position according to the international 10-20 system. EEG data were sampled at 512 Hz and preprocessed in real-time as 2000 ms epochs, including band-pass filtering (high-pass: 2 Hz, low-pass: 32 Hz, notch: 50 Hz), artifact removal, independent components analysis, entropy calculation, signal reconstruction, and standardization software. For both the intervention and sham control conditions, background audio of a flowing stream was played through stereo earphones while EEG data were collected. The predominant baseline EEG frequency was computed during the first 2 minutes of each session. As disclosed herein, binaural beats were delivered at subliminal intensity with a 144 Hz monotone to the left ear and a tone of 144 Hz plus the predominant baseline frequency to the right ear. As the EEG activity stabilized, the binaural beat frequency was gradually decreased at 1 -minute intervals while continuously monitoring EEG data to ensure the predominant frequency followed the binaural frequency. When predominant EEG activity reached 4 Hz (the target state), the binaural beat frequency was maintained at this level for the remainder of the 30-minute session, with adjustments as needed to guide the predominant frequency back to 4 Hz if it deviated. In the sham control condition, EEG monitoring was conducted identically; however, instead of binaural beats with different frequencies, a subliminal 144 Hz monotone was played into both ears simultaneously for 30 minutes.

[0141] EEG data were continuously recorded during the intervention and control sessions to objectively assess participants' brain states. EEG metrics were evaluated to provide objective physiological evidence of relaxation and sleep states. These included:• Time to target frequency: Time (in seconds) for participants to reach the relaxed state (< 8 Hz, corresponding to alpha / theta states associated with relaxation);• Sleep induction metrics: Assessed whether participants reached the following states: relaxed state (i.e., < 8 Hz at least once during the session), sustained relaxed state (i.e., predominant frequency < 8 Hz lasting for at least 3 consecutive minutes), deep relaxed state (i.e., predominant frequency < 4 Hz at least once) and deep relaxed / sleep state (i.e., predominant frequency < 4 Hz sustained for at least 3 minutes); and• Frequency distribution: he distribution of predominant EEG frequencies across time at baseline (Os), 300s, 600s, 900s, 1200s, 1500s, last 5 minutes, and the final recording, categorized into frequency bands (i.e., delta: 0-4 Hz, theta: 4-8 Hz, low alpha: 8-10 Hz, high alpha: 10-13 Hz, and beta: 13-30 Hz).

[0142] Subjective perceptions were assessed using visual analogue scales (VAS) administered before and after each session. Five 100 mm VAS were used to measure perceived relaxation, sleepiness, focus, cognitive performance, and overall well-being, with anchors at 0 and 100 mm.

[0143] A Stop Signal Reaction Time (SSRT) task combined a primary go task, and a secondary stop task were assigned to participants. Each trial began with a fixation cross (2500 ms ± 1500 ms), followed by either the letter X or O (500 ms duration), to which participants were instructed to press designated response buttons. In one-third of trials, the background turned red 250 ms after letter onset (stop signal delay; SSD), indicating participants should withhold their response. In the remaining trials, the background remained white (go trials). The SSD was dynamically adjusted, increasing by 50 ms following successful inhibition and decreasing by 50 ms following failed inhibition. The task comprised 90 trials (60 go trials, 30 stop trials). Several parameters were derived from the SSRT task using a drift diffusion modeling approach. These parameters were:• Stop Signal Reaction Time (SSRT): The primary measure of inhibitory control, representing the latency of the stop process. Lower SSRT values indicate better inhibitory control.• Boundary separation (at): In go trials, represents the response caution or decision threshold. Larger values indicate more cautious decision-making, with more information accumulated before a response.• Drift rate (v : In go trials, reflects the rate of information accumulation. Higher values indicate more efficient information processing.• Starting point (zt): In go trials, indicates the initial bias toward one response over another. Values closer to 0.5 suggest unbiased processing.• Boundary separation in stop trials (a2): Similar to ai but specific to stop trials. Higher values suggest increased caution during inhibitory processing.• Drift rate in stop trials (v2): Reflects the efficiency of the stopping process. More negative values indicate stronger inhibitory signals.• Starting point in stop trials (z2): The initial bias in stop trials, with values closer to 0 indicating a bias toward stopping.

[0144] Participants were also given a novelty encoding task. This task utilized complex visual stimuli created by placing combinations of shapes (circles, triangles, squares) and colors (red, green, blue) within a 3x3 matrix. The task consisted of three phases: familiarization phase in which five basic images were presented five times each; incidental learning phase in which the participants viewed the original basic images along with novel variations (color changes, shape changes, or both) derived from the basic images; and a recognition phase in which the participants viewed previously shown novel images and entirely new novel images derived from unseen basic images. Each image was shown for 3000 ms with jittered interstimulus intervals (1000 ms ± 500 ms). Participants were instructed to press a key if they saw an image that was seen before during the day. Novel images were used for each administration of the task to minimize biases associated with familiarization with the images from prior administrations. Several performance metrics were analyzed to characterize different aspects of memory encoding and retrieval:• Hit Rate (HR): The proportion of correctly identified targets (true positives). Higher values indicate better recognition of previously seen stimuli.• False Alarm Rate (FA): The proportion of non-targets incorrectly identified as targets (false positives). Lower values indicate better discrimination.• d-Prime: A sensitivity index from signal detection theory that measures the ability to discriminate signals (targets) from noise (non-targets). Higher values indicate better perceptual sensitivity.• Response Bias (RB): A measure of the general tendency to respond "yes" or "no" regardless of stimulus type. Positive values indicate a conservative bias (tendency to respond "no"), while negative values indicate a liberal bias (tendency to respond"yes").• Beta: Another measure of response criterion that is less affected by sensitivity. Higher values indicate a more conservative response strategy.• Precision: The proportion of correct positive identifications out of all positive identifications. Higher values indicate higher accuracy when identifying targets.• Specificity: The proportion of correctly rejected non-targets (true negatives). Higher values indicate better ability to correctly identify non-targets.• F1 Score: The harmonic mean of precision and recall (hit rate), providing a balanced measure of performance. Higher values indicate better overall performance.• Reaction Time (RT): The time taken to respond to stimuli, with faster times generally indicating more efficient processing.

[0145] Data were analyzed using linear mixed-effects models. The models accounted for the nested nature of the data within subjects (repeated measures) and included fixed effects for condition (intervention vs. control), time (pre vs. post), and their interaction. For the EEG data, the proportion of participants reaching target frequency states (< 8 Hz and < 4 Hz) and the median time (with interquartile range) to reach each brain state was calculated. Frequency distributions across different time points were analyzed to track the progression of brain states throughout the session. Comparisons between intervention and control conditions were made using appropriate non-parametric tests for proportional data. For behavioral and subjective measures, F-statistics with degrees of freedom and p-values were reported. Results were considered statistically significant at p < 0.05, with trends noted at p < 0.10.

[0146] The predominant EEG frequency was not significantly different between the intervention and sham control conditions at baseline (17.92 ± 2.74 Hz and 18.44 ± 2.60 Hz respectively; p =0.520; Table 1 ). A consistent, rapid decrease in the predominant brain single electrode EEG frequency band was noted in all participants with the intervention compared to the sham control condition until the pre-awakening state. When the participants were exposed to a 32 Hz frequency during the intervention condition with the aim of awakening the participants, the mean predominant frequency increased from 2.72 ± 0.84 Hz to 12.16 ±7.05 Hz (i.e. from delta frequency range to the high alpha frequency range) by the time of conclusion of the intervention. Table 1 provides a comparison of mean predominant frequencies (Hz) between the intervention and sham-control conditions.Table 1

[0147] The distributions of the predominant brain frequency of the participants as determined by the single electrode EEG are shown in Table 2.Table 2: EEG frequency band distribution between the intervention and sham control conditions

[0148] At baseline, all participants in both groups exhibited beta-dominant (13-30 Hz) activity. Following the introduction of the EEG-guided binaural beat intervention, a rapid frequency downshift was observed in the intervention group, with 72% of participants transitioning from beta to slower frequency bands within 5 minutes. All participants in the intervention condition successfully reached < 8 Hz (i.e., a relaxed state), with a median time of 441 .6 seconds (i.e., 7.4 minutes) and stayed at < 8 Hz frequency for > 3 minutes. By the 10-minute mark, 80% of intervention participants reached delta frequencies (0-4 Hz), increasing to 96% by 20 minutes. Twenty-four out of the 25 participants reached < 4 Hz frequency (i.e., deep relaxation) within a median duration of 541 .6 seconds (i.e., 9 minutes) with the intervention and 22 participants were able to maintain the < 4 Hz frequency for at least 3 minutes. During the pre-awakening period, 92% of intervention participants exhibited delta activity, while upon awakening, a return to faster frequencies was observed with 52% shifting back to beta and 36% to theta bands. In contrast, the control group maintained predominantly beta activity (88-96%) throughout the session, with minimal transitions to slower frequencies. While three participants in the control condition also reached < 8 Hz, this was achieved at a median duration of 723.8 seconds (i.e., 12.1 minutes), only one participant sustained the predominant frequency at < 8 Hz for at least 3 minutes. Only one participant (4%) was able to reach the < 4 Hz range, after 1080 seconds (i.e., 18 minutes), yet this frequency did not sustain for 3 minutes. These findings demonstrate the effectiveness of the real-time EEG-guided binaural beat intervention in rapidly inducing and maintaining sleep- associated brain states compared to the sham control condition.

[0149] Results of the stop signal reaction task are summarized in Table 3.Table 3: Comparison of stop signal reaction task outcomes between the intervention and sham-control conditions

[0150] During the intervention, mean SSRT improved (i.e., decreased), while worsening (i.e., increase) of mean SSRT was seen with the control condition resulting in a statistical trend in the interaction (FI,68.8 = 2.82, p = 0.098). This finding suggested a statistical trend of improvement of inhibitory control following exposure to the intervention. Analysis of drift diffusion parameters confirmed the above finding. Specifically, a mean increase in boundary separation while considering stop trials was seen with the intervention, while a decrease inmean boundary separation was observed with exposure to the control condition resulting in a statistical trend in the interaction (FI,68.O = 3.52, p = 0.065). This suggested that exposure to the intervention was associated with enhanced cognitive caution during stop trials, allowing more evidence to be accumulated before making decisions, which could translate to fewer impulsive actions. Exposure to the intervention was also associated with a mean decrease in inhibitory drift rate, while the control condition was associated with an increase in the inhibitory drift rate, resulting in a significant main effect of time (FI ,69.5 = 4.80, p = 0.032) and a statistical trend of the interaction (FI,69.8 = 3.40, p = 0.070), indicating improved efficiency in processing stop signals with the intervention.

[0151] Results of the novelty encoding task are summarized in Table 4.Table 4: Comparison of novelty encoding task outcomes between the intervention and sham-control conditions

[0152] The intervention was associated with improved reaction time performance compared to the control condition, with a significant interaction effect (FI ,54.4 = 4.50, p = 0.039). Specifically, mean reaction time decreased from 1.23s to 1.10s in the intervention group, while slightly increasing from 1 .13s to 1 .16s in the control group. This finding suggests enhanced information processing speed following the binaural beat intervention. Both groups showed improvements in false alarm rates (and consequently, specificity) across time, with a significant main effect of time (F1 ,57.2 = 4.18, p = 0.046) but no significant interaction. Similarly, response bias showed a trend toward more conservative decision-making in both groups over time (FI,56.2 = 3.26, p = 0.077). Other cognitive performance measures including hit rate, d-prime, precision, and F1 score showed numerical improvements in the intervention group, but these changes did not reach statistical significance compared to the control condition. Collectively, these results indicate that the EEG-guided binaural beat intervention primarily enhanced information retrieval speed while maintaining accuracy metrics.

[0153] Results of the subjective visual analogue scales are summarized in Table 5.Table 5: Comparison of subjective visual analogue scale outcomes between the intervention and sham-control conditions

[0154] For relaxation ratings, a highly significant main effect of time was observed (F1 ,72 = 15.02, p < 0.001 ), with both groups reporting increased relaxation following the session (control: 68.4 to 83.6; intervention: 67.0 to 78.0), but no significant interaction effect. Similarly, there was a strong main effect of time for sleepiness (F1 ,72 = 33.73, p < 0.001 ), with both groups reporting substantially increased sleepiness after the session, though the increase appeared somewhat larger in the control group (22.5 to 59.2) compared to the intervention group (31.5 to 53.5). Both groups reported decreased focus over time (F1 ,72 = 6.78, p = 0.011 ), consistent with the increased relaxation and sleepiness. For self-reported cognitive performance, there was a significant main effect of time (F1 ,72 = 4.99, p = 0.029) and a marginally significant interaction (F1 ,72 = 2.79, p = 0.099). The control group reported a decrease in perceived cognitive performance (69.3 to 62.2), while the intervention group maintained relatively stable ratings (66.9 to 67.3). No significant effects were observed for general well-being ratings. These results suggest that while both conditions induced relaxation and sleepiness, the intervention may have helped maintain subjective cognitive performance despite the relaxation effects, aligning with the objective task performance findings on the novelty encoding and stop signal reaction time tasks.

[0155] The results of the study underscore the efficacy of the embodiments disclosedherein, and demonstrate that the real-time EEG-guided binaural beat systems and methods as disclosed effectively induced target brain states with striking superiority over the sham control. The intervention successfully guided all participants (100%) to relaxed states (i.e., <8 Hz) and 96% to deep relaxed states (i.e., <4 Hz), compared to only 12% and 4% in the control condition, respectively. The intervention also achieved these states significantly faster, with median times approximately half those observed in the control condition. These physiological changes were accompanied by improved cognitive performance, particularly in domains requiring inhibitory control and information processing. Stop signal task results revealed trends of enhanced response inhibition (decreased SSRT) and improved decision thresholds (increased a2) following the intervention, while novelty encoding task results showed significantly faster reaction times without sacrificing accuracy. Interestingly, these cognitive improvements occurred despite increased subjective relaxation and sleepiness, suggesting the intervention facilitated a beneficial state of "relaxed alertness" that selectively enhanced multiple cognitive domains.

[0156] FIGS. 10-12 are provided as exemplary diagrams of data-processing environments in which embodiments may be implemented. It should be appreciated that FIGS. 10-12 are only exemplary and are not intended to assert or imply any limitation with regard to the environments in which aspects or embodiments of the disclosed embodiments may be implemented. Many modifications to the depicted environments may be made without departing from the spirit and scope of the disclosed embodiments.

[0157] A block diagram of a computer system 1000 that executes programming for implementing parts of the methods and systems disclosed herein is provided in FIG. 10. A computing device in the form of a computer 1010 configured to interface with controllers, peripheral devices, and other elements disclosed herein may include one or more processing units 1002, memory 1004, removable storage 1012, and non-removable storage 1014. Memory 1004 may include volatile memory 1006 and non-volatile memory 1008. Computer 1010 may include or have access to a computing environment that includes a variety of transitory and non-transitory computer-readable media such as volatile memory 1006 and non-volatile memory 1008, removable storage 1012 and non-removable storage 1014. Computer storage includes, for example, random access memory (RAM), read only memory(ROM), erasable programmable read-only memory (EPROM) and electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD ROM), Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage, or other magnetic storage devices, or any other medium capable of storing computer-readable instructions, as well as data including image data.

[0158] Computer 1010 may include, or have access to, a computing environment that includes input 1016, output 1018, and a communication connection 1020. The computer may operate in a networked environment using a communication connection 1020 to connect to one or more remote computers, remote sensors and / or controllers, detection devices, handheld devices, multi-function devices (MFDs), speakers, mobile devices, tablet devices, mobile phones, Smartphone, or other such devices. The remote computer may also include a personal computer (PC), server, router, network PC, RFID enabled device, a peer device or other common network node, or the like. The communication connection may include a Local Area Network (LAN), a Wide Area Network (WAN), Bluetooth connection, or other networks. This functionality is described more fully in the description associated with FIG. 11 below.

[0159] Output 1018 is most commonly provided as a computer monitor, but may include any output device. Output 1018 and / or input 1016 may include a data collection apparatus associated with computer system 1000. In addition, input 1016, which commonly includes a computer keyboard and / or pointing device such as a computer mouse, computer track pad, or the like, allows a user to input instructions to computer system 1000. A user interface can be provided using output 1018 and input 1016. Output 1018 may function as a display for displaying data and information for a user, and for interactively displaying a graphical user interface (GUI) 1030.

[0160] Note that the term “GUI” generally refers to a type of environment that represents programs, files, options, and so forth by means of graphically displayed icons, menus, and dialog boxes on a computer monitor screen. A user can interact with the GUI to select and activate such options by directly touching the screen and / or pointing and clicking with a userinput device 1016 such as, for example, a pointing device such as a mouse, and / or with a keyboard. A particular item can function in the same manner to the user in all applications because the GUI provides standard software routines (e.g., program module or node 1025) to handle these elements and report the user’s actions. The GUI can further be used to display the electronic service image frames as discussed below.

[0161] Computer-readable instructions, for example, program module or node 1025, which can be representative of other modules or nodes described herein, are stored on a computer- readable medium and are executable by the processing unit 1002 of computer 1010. Program module or node 1025 may include a computer application. A hard drive, CD-ROM, RAM, Flash Memory, and a USB drive are just some examples of articles including a computer-readable medium.

[0162] FIG. 11 depicts a graphical representation of a network of data-processing systems 1 100 in which aspects of the present invention may be implemented. Network data- processing system 1 100 can be a network of computers or other such devices, such as mobile phones, smart phones, sensors, controllers, actuators, speakers, “internet of things” devices, and the like, in which embodiments of the present invention may be implemented. Note that the system 1100 can be implemented in the context of a software module such as program module or node 1025. The system 1100 includes a network 1102 in communication with one or more clients 1110, 11 12, and 1114. Network 1 102 may also be in communication with one or more devices 1104, servers 1 106, and storage 1108. Network 1102 is a medium that can be used to provide communications links between various devices and computers connected together within a networked data processing system such as computer system 1000. Network 1 102 may include connections such as wired communication links, wireless communication links of various types, and fiber optic cables. Network 1102 can communicate with one or more servers 1 106, one or more external devices such as device 1 104, and a memory storage unit such as, for example, memory or database 1108. It should be understood that device 1 104 may be embodied as an EEG device, audio device, headphones, earphones, detector device, magnetic detector, electronic conditioning system, controller, receiver, transmitter, transceiver, transducer, driver, signal generator, testing apparatus, or other such device.

[0163] In the depicted example, device 1 104, server 1 106, and clients 11 10, 1 1 12, and 1 114 connect to network 1102 along with storage unit 1108. Clients 1 110, 1 112, and 11 14 may be, for example, personal computers or network computers, handheld devices, mobile devices, tablet devices, smart phones, personal digital assistants, controllers, recording devices, speakers, MFDs, etc. Computer system 1000 depicted in FIG. 10 can be, for example, a client such as client 11 10 and / or 11 12 and / or 1114.

[0164] Computer system 1000 can also be implemented as a server such as server 1 106, depending upon design considerations. In the depicted example, server 1 106 provides data such as boot files, operating system images, applications, and application updates to clients 1 110, 1112, and / or 1114. Clients 1110, 1112, and 1 1 14 and device 1104 are clients to server 1 106 in this example. Network data-processing system 1100 may include additional servers, clients, and other devices not shown. Specifically, clients may connect to any member of a network of servers, which provide equivalent content.

[0165] In the depicted example, network data-processing system 1100 is the Internet, with network 1102 representing a worldwide collection of networks and gateways that use the Transmission Control Protocol / lnternet Protocol (TCP / IP) suite of protocols to communicate with one another. At the heart of the Internet is a backbone of high-speed data communication lines between major nodes or host computers consisting of thousands of commercial, government, educational, and other computer systems that route data and messages. Of course, network data-processing system 1100 may also be implemented as a number of different types of networks such as, for example, an intranet, a local area network (LAN), or a wide area network (WAN). FIGS. 10 and 11 are intended as examples and not as architectural limitations for different embodiments of the present invention.

[0166] FIG. 12 illustrates a software system 1200, which may be employed for directing the operation of the data-processing systems such as computer system 1000 depicted in FIG. 10. Software application 1205, may be stored in memory 1004, on removable storage 1012, or on non-removable storage 1014 shown in FIG. 10, and generally includes and / or is associated with a kernel or operating system 1210 and a shell or interface 1215. One or moreapplication programs, such as module(s) or node(s) 1025, may be "loaded" (i.e., transferred from removable storage 101 , or on non-removable storage 1014 into the memory 1004) for execution by the data-processing system 1000. The data-processing system 1000 can receive user commands and data through user interface 1215, which can include input 1016 and output 1018, accessible by a user 1220. These inputs may then be acted upon by the computer system 1000 in accordance with instructions from operating system 1210 and / or software application 1205 and any program module(s) or node(s) 1025 thereof.

[0167] Generally, program modules (e.g., program module(s) or node(s) 1025) can include, but are not limited to, routines, subroutines, software applications, programs, objects, components, data structures, etc., that perform particular tasks or implement particular abstract data types and instructions. Moreover, those skilled in the art will appreciate that elements of the disclosed methods and systems may be practiced with other computer system configurations such as, for example, hand-held devices, mobile phones, smart phones, tablet devices multi-processor systems, microcontrollers, printers, copiers, fax machines, multi-function devices, data networks, microprocessor-based or programmable consumer electronics, networked personal computers, minicomputers, mainframe computers, servers, medical equipment, medical devices, and the like.

[0168] Note that the term “module” or “node” as utilized herein may refer to a collection of routines and data structures that perform a particular task or implements a particular abstract data type. Modules may be composed of two parts: an interface, which lists the constants, data types, variables, and routines that can be accessed by other modules or routines; and an implementation, which is typically private (accessible only to that module), and which includes source code that actually implements the routines in the module. The term module may also simply refer to an application such as a computer program designed to assist in the performance of a specific task such as word processing, accounting, inventory management, etc., or a hardware component designed to equivalently assist in the performance of a task.

[0169] The interface 1215 (e.g., a graphical user interface 1030) can serve to display results, whereupon a user 1220 may supply additional inputs or terminate a particular session. In some embodiments, operating system 1210 and GUI 1030 can be implementedin the context of a “windows” system. It can be appreciated, of course, that other types of systems are possible. For example, rather than a traditional “windows” system, other operation systems such as, for example, a real-time operating system (RTOS) more commonly employed in wireless systems may also be employed with respect to operating system 1210 and interface 1215. The software application 1205 can include, for example, module(s) or node(s) 1025, which can include instructions for carrying out steps or logical operations such as those shown and described herein.

[0170] The following description is presented with respect to embodiments of the present invention, which can be embodied in the context of, or require the use of, a data-processing system such as computer system 1000, in conjunction with program module or node 1025, and data-processing system 1 100 and network 1102 depicted in FIGS. 10-8. The present invention, however, is not limited to any particular application or any particular environment. Instead, those skilled in the art will find that the system and method of the present invention may be advantageously applied to a variety of system and application software including database management systems, word processors, and the like. Moreover, the present invention may be embodied on a variety of different platforms including Windows, Macintosh, UNIX, LINUX, Android, Arduino, LabView and the like. Therefore, the descriptions of the exemplary embodiments, which follow, are for purposes of illustration and not considered a limitation.

[0171] Based on the foregoing, it can be appreciated that a number of embodiments, preferred and alternative, are disclosed herein. In an embodiment, a system for electroencephalography (EEG) biofeedback comprising an EEG signal capturing device comprising an active recording electrode, and a computer system, the computer system further comprising: at least one processor, a user interface, and a computer-usable medium embodying computer program code, the computer-usable medium capable of communicating with the at least one processor, the computer program code comprising instructions executable by the at least one processor and configured for: receiving an EEG signal, identifying a current predominant brain frequency in the EEG signal, causing a base frequency to be played in stereo by an audio device comprising a first side output and a second side output, causing a modified frequency to be played by the first side output of theaudio device, until the current predominant brain frequency matches a difference between the base frequency and the modified frequency, and causing at least one additional modified frequency to be played by the first side output of the audio device, until the current predominant brain frequency matches a difference between the base frequency and the at least one additional modified frequency. In an embodiment, the at least one additional modified frequency comprises a plurality of additional modified frequencies, wherein the instructions executable by the at least one processor is configured for causing each of the plurality of additional modified frequencies to be played by the first side output of the audio device in series, until the current predominant brain frequency matches a last of the plurality of additional modified frequencies. In an embodiment, the last of the plurality of modified frequencies comprises a target brainwave bandwidth. In an embodiment, the computer program code comprising instructions executable by the at least one processor is further configured for accepting input indicative of the target brainwave bandwidth. In an embodiment, the target brainwave bandwidth comprises one of: Delta waves of 0.1 to 4 Hz, Theta waves of 4 to 8 Hz, Low Alpha waves of 8 to 10 Hz, High Alpha waves of 10 to 14 Hz, Beta waves of 14 to 30 Hz and Gamma waves of 30 to 100 Hz. In an embodiment, the instructions executable by the at least one processor is configured for causing the second side output of the audio device to continually play the base frequency wherein the base frequency differs from the modified frequency. In an embodiment, the difference between the monotone base frequency and the modified frequency creates a binaural beat. In an embodiment, the EEG signal capturing device further comprises a headband, a ground electrode, and a reference electrode. In an embodiment, the EEG signal capturing device further comprises an amplifier for amplifying the EEG signal and a transmitter for transmitting the EEG signal. In an embodiment, the computer program code comprising instructions executable by the at least one processor is further configured for eliminating artifacts in the EEG signal, and applying a band pass filter to the EEG signal in order to generate a processed EEG signal. In an embodiment, the computer program code comprising instructions executable by the at least one processor is further configured for generating a power spectra for the EEG signal.

[0172] In an embodiment, a computer implemented method for electroencephalography(EEG) biofeedback comprising receiving an EEG signal from an EEG signal capturing device, identifying a current predominant brain frequency in the EEG signal, causing a base frequency to be played in stereo by an audio device comprising a first side output and a second side output, causing a modified frequency to be played by the first side output of the audio device, until the current predominant brain frequency matches a difference between the base frequency and the modified frequency, and causing at least one additional modified frequency to be played by the first side output of the audio device, until the current predominant brain frequency matches a difference between the base frequency and the at least one additional modified frequency. In an embodiment, the at least one additional modified frequency comprises a plurality of additional modified frequencies, the method further comprising causing each of the plurality of additional modified frequencies to be played by the first side output of the audio device in series, until the current predominant brain frequency matches a last of the plurality of additional modified frequencies. In an embodiment, each of the plurality of additional modified frequencies comprises a frequency equidistant from its neighboring frequencies in one of an ascending or descending series. In an embodiment, the last of the plurality of additional modified frequencies comprises a target brainwave frequency bandwidth. In an embodiment, the computer implemented method for EEG biofeedback further comprises causing the second side output of the audio device to continually play the base frequency, wherein the base frequency differs from the modified frequency, wherein the difference between the base frequency and the modified frequency creates a binaural beat. In an embodiment, the computer implemented method for EEG biofeedback further comprises eliminating artifacts in the EEG signal, and applying a band pass filter to the EEG signal in order to generate a processed EEG signal. In an embodiment, the computer implemented method for EEG biofeedback further comprises generating a power spectra for the EEG signal.

[0173] In an embodiment, a system for electroencephalography (EEG) biofeedback comprises an EEG signal capturing device comprising an electrode, an amplifier, and a transmitter for transmitting an EEG signal, an audio device comprising a first side output and a second side output, and a computer system, the computer system further comprising: at least one processor, a user interface, and a computer-usable medium embodying computerprogram code, the computer-usable medium capable of communicating with the at least one processor, the computer program code comprising instructions executable by the at least one processor and configured for: receiving an EEG signal from the EEG signal capturing device, identifying a current predominant brain frequency in the EEG signal, causing a base frequency to be played by the audio device, and causing a modified frequency to be played by the first side output of the audio device, until the current predominant brain frequency matches a difference between the base frequency and the modified frequency. In an embodiment, the difference between the base frequency and the modified frequency creates a binaural beat.

[0174] In an embodiment, a wearable headset device for biofeedback comprises a wearable head mount, an anode associated with the wearable head mount, at least one cathode associated with the wearable head mount, at least one active electrode associated with the wearable head mount, at least one reference electrode associated with the wearable head mount, at least one ground electrode associated with the wearable head mount, an output associated with the wearable head mount, and a microcontroller configured to receive input from the at least one active electrode associated with the wearable head mount, at least one reference electrode associated with the wearable head mount, at least one ground electrode associated with the wearable head mount, and generate an output signal to the output associated with the wearable head mount device. In an embodiment, the wearable headset device for biofeedback further comprises configuring the at least one active electrode in the wearable head mount to be positioned within a 2.5 cm radius of an Fp1 position or an Fp2 position in a 10-20 electrode system. In an embodiment, the wearable headset device for biofeedback further comprises configuring the at least one reference electrode in the wearable head mount to be positioned substantially within 2.5 cm of a temporal chain of a 10-20 electrode system, the temporal chain comprising F7, T3, T5 and 01 positions on a left side and F8, T4, T6 and 02 positions on a right side. In an embodiment at least one of the anode and the at least one cathode is configured to deliver an electrical vector. In an embodiment, the electrical vector comprises one of a continuous electrical vector and a pulsed electrical vector. In an embodiment, the anode and the at least one cathode are configured to provide an electrical vector substantially between an Fp1 positionand nasion in a 10-20 electrode system. In an embodiment, the wearable headset device for biofeedback further comprises configuring the anode in the wearable head mount to be positioned substantially between an Fp1 position and nasion in a 10-20 electrode system. In an embodiment, the wearable headset device for biofeedback further comprises configuring the anode in the wearable head mount to be positioned substantially within 2.5 cm of either side of a mid-sagittal plane. In an embodiment, the wearable headset device for biofeedback further comprise configuring the cathodes in the wearable head mount to be positioned bilaterally with substantial symmetry to each other over a temporal region or an occipital region. In an embodiment, the wearable headset device for biofeedback further comprises an amplifier configured to amplify signals collected by the at least one active electrode associated with the wearable head mount, the at least one reference electrode associated with the wearable head mount, or the at least one ground electrode associated with the wearable head mount. In an embodiment, the output further comprises at least one of a binaural audio device and a bitemporal bone vibrator. In an embodiment, the wearable headset device for biofeedback further comprises configuring the output in the wearable head mount to be positioned substantially over the temporal bone.

[0175] In an embodiment, a wearable headset device for biofeedback comprises an anode associated, at least one cathode associated with the wearable head mount, wherein the anode and the at least one cathode are configured to deliver an electrical vector, at least one active electrode, at least one reference electrode, at least one ground electrode, and a microcontroller configured to receive input from the at least one active electrode, at least one reference electrode, and at least one ground electrode, and generate an output signal to an output associated with the wearable head mount device. In an embodiment, the wearable headset device comprises configuring the at least one active electrode in the wearable head mount to be positioned within a 2.5 cm radius of an Fp1 position or an Fp2 position in a I Q- 20 electrode system. In an embodiment, the wearable headset device comprises configuring the at least one reference electrode in the wearable head mount to be positioned substantially within 2.5 cm of a temporal chain of a 10-20 electrode system, the temporal chain comprising F7, T3, T5 and 01 positions on a left side and F8, T4, T6 and 02 positions on a right side. In an embodiment, the anode and the at least one cathode are configured to provide anelectrical vector substantially between an Fp1 position and nasion in a 10-20 electrode system. In an embodiment, the wearable headset device comprises configuring the anode in the wearable head mount to be positioned in at least one location comprising a location substantially between an Fp1 position and nasion in a 10-20 electrode system and a location substantially within 2.5 cm of either side of a mid-sagittal plane. In an embodiment, the wearable headset device comprises configuring the cathodes in the wearable head mount to be positioned bilaterally with substantial symmetry to each other over at least one of a temporal region, and an occipital region. In an embodiment, the wearable headset device comprises an amplifier configured to amplify signals collected by the at least one active electrode associated with the wearable head mount, the at least one reference electrode associated with the wearable head mount, or the at least one ground electrode associated with the wearable head mount.

[0176] A system for biofeedback comprises a wearable head mount, an anode associated with the wearable head mount, at least one cathode associated with the wearable head mount at least one active electrode associated with the wearable head mount, at least one reference electrode associated with the wearable head mount, an output associated with the wearable head mount device, and a microcontroller configured to receive input from the at least one active electrode associated with the wearable head mount, at least one reference electrode associated with the wearable head mount, at least one ground electrode associated with the wearable head mount, and generate an output signal to the output associated with the wearable head mount device.

[0177] It will be appreciated that variations of the above-disclosed and other features and functions, or alternatives thereof, may be desirably combined into many other different systems or applications. Also, it should be appreciated that various presently unforeseen or unanticipated alternatives, modifications, variations, or improvements therein may be subsequently made by those skilled in the art which are also intended to be encompassed by the following claims.

Claims

CLAIMSWhat is claimed is:1 . A system for electroencephalography (EEG) biofeedback comprising: an EEG signal capturing device comprising an active recording electrode; and a computer system, the computer system further comprising: at least one processor; a user interface; and a computer-usable medium embodying computer program code, the computer- usable medium capable of communicating with the at least one processor, the computer program code comprising instructions executable by the at least one processor and configured for: receiving an EEG signal; identifying a current predominant brain frequency in the EEG signal; causing a base frequency to be played in stereo by an audio device comprising a first side output and a second side output; causing a modified frequency to be played by the first side output of the audio device, until the current predominant brain frequency matches a difference between the base frequency and the modified frequency; and causing at least one additional modified frequency to be played by the first side output of the audio device, until the current predominant brain frequency matches a difference between the base frequency and the at least one additional modified frequency.

2. The system for EEG biofeedback of claim 1 wherein the at least one additional modified frequency comprises a plurality of additional modified frequencies, wherein the instructions executable by the at least one processor is configured for: causing each of the plurality of additional modified frequencies to be played by the first side output of the audio device in series, until the current predominant brain frequency matches a last of the plurality of additional modified frequencies.

3. The system for EEG biofeedback of claim 2 wherein the last of the plurality of modified frequencies comprises a target brainwave bandwidth.

4. The system for EEG biofeedback of claim 3 wherein the computer program code comprising instructions executable by the at least one processor is further configured for: accepting input indicative of the target brainwave bandwidth.

5. The system for EEG biofeedback of claim 3 wherein the target brainwave bandwidth comprises one of:Delta waves of 0.1 to 4 Hz;Theta waves of 4 to 8 Hz;Low Alpha waves of 8 to 10 Hz;High Alpha waves of 10 to 14 Hz;Beta waves of 14 to 30 Hz; andGamma waves of 30 to 100 Hz.

6. The system for EEG biofeedback of claim 1 wherein the instructions executable by the at least one processor is configured for: causing the second side output of the audio device to continually play the base frequency wherein the base frequency differs from the modified frequency.

7. The system for EEG biofeedback of claim 6 wherein the difference between the base frequency and the modified frequency creates a binaural beat.

8. The system for EEG biofeedback of claim 1 wherein the EEG signal capturing device further comprises: a headband; a ground electrode; and a reference electrode.

9. The system for EEG biofeedback of claim 1 wherein the EEG signal capturing device further comprises: an amplifier for amplifying the EEG signal; and a transmitter for transmitting the EEG signal.

10. The system for EEG biofeedback of claim 1 wherein the computer program code comprising instructions executable by the at least one processor is further configured for: eliminating artifacts in the EEG signal; and applying a band pass filter to the EEG signal in order to generate a processed EEG signal.1 1 . The system for EEG biofeedback of claim 1 wherein the computer program code comprising instructions executable by the at least one processor is further configured for: generating a power spectra for the EEG signal.

12. A wearable headset device for biofeedback comprising: an anode; at least one cathode, wherein the anode and the at least one cathode are configured to deliver an electrical vector; at least one active electrode; at least one reference electrode; at least one ground electrode; and a microcontroller configured to receive input from the at least one active electrode, at least one reference electrode, and at least one ground electrode, and generate an output signal to an output associated with the wearable headset device.

13. The wearable headset device for biofeedback of claim 12 further comprising: configuring the at least one active electrode in the wearable headset device to be positioned within a 2.5 cm radius of an Fp1 position or an Fp2 position in a 10-20 electrode system.

14. The wearable headset device for biofeedback of claim 12 further comprising: configuring the at least one reference electrode in the wearable headset device to be positioned substantially within 2.5 cm of a temporal chain of a 10-20 electrode system, the temporal chain comprising F7, T3, T5 and 01 positions on a left side and F8, T4, T6 and 02 positions on a right side.

15. The wearable headset device for biofeedback of claim 12 wherein the anode and the at least one cathode are configured to provide an electrical vector substantially between an Fp1 position and nasion in a 10-20 electrode system.

16. The wearable headset device for biofeedback of claim 12 further comprising: configuring the anode in the wearable headset device to be positioned in at least one location comprising: a location substantially between an Fp1 position and nasion in a 10-20 electrode system; and a location substantially within 2.5 cm of either side of a mid-sagittal plane.

17. The wearable headset device for biofeedback of claim 12 further comprising: configuring the at least one cathode in the wearable headset device to be positioned bilaterally with substantial symmetry to each other over at least one of: a temporal region; and an occipital region.

18. The wearable headset device for biofeedback of claim 12 further comprising: an amplifier configured to amplify signals collected by the at least one active electrode associated with the wearable headset device, the at least one reference electrode associated with the wearable headset device, or the at least one ground electrode associated with the wearable headset device.

19. A computer implemented method for electroencephalography (EEG) biofeedback comprising:receiving an EEG signal from an EEG signal capturing device; identifying a current predominant brain frequency in the EEG signal; causing a base frequency to be played in stereo by an audio device comprising a first side output and a second side output; causing a modified frequency to be played by the first side output of the audio device, until the current predominant brain frequency matches a difference between the base frequency and the modified frequency; and causing at least one additional modified frequency to be played by the first side output of the audio device, until the current predominant brain frequency matches a difference between the base frequency and the at least one additional modified frequency.

20. The computer implemented method for EEG biofeedback of claim 19 wherein the at least one additional modified frequency comprises a plurality of additional modified frequencies, the method further comprising: causing each of the plurality of additional modified frequencies to be played by the first side output of the audio device in series, until the current predominant brain frequency matches a last of the plurality of additional modified frequencies.21 . The computer implemented method for EEG biofeedback of claim 20 wherein each of the plurality of additional modified frequencies comprises a frequency equidistant from its neighboring frequencies in one of an ascending or descending series.

22. The computer implemented method for EEG biofeedback of claim 20 wherein the last of the plurality of additional modified frequencies comprises a target brainwave frequency bandwidth.

23. The computer implemented method for EEG biofeedback of claim 19 further comprising: causing the second side output of the audio device to continually play the base frequency, wherein the base frequency differs from the modified frequency, wherein the difference between the base frequency and the modified frequency creates a binaural beat.

Images