The system of the present invention includes at least one brain signal capturing device, at least one memory device for storing software instructions, and at least one processor. The processor is in communication with the brain signal capturing device and executes the instructions stored on the memory. The instructions include the steps of analyzing a user's brain signal patterns and searching based on the user's brain signals.

A notification control method, system, and non-transitory computer readable medium, include a state of flow detecting circuit configured to detect a state of flow of brain waves of a user from user data, a notification priority setting circuit configured to set a notification priority setting by ranking a type of a notification to be delivered to a user device according to an importance of a message associated with the notification, and a notification control circuit configured to control the notification to be output on the user device at an allowable time based on a rank of the notification priority setting being higher than a rank of the state of flow of the user.

A method and apparatus using brainwaves to control real objects is provided. The method and apparatus comprise using sensors to detect the brain's electrical signals and transmit at least two brainwaves to an apparatus that converts the brainwaves into a format usable by a signal processor. The signal processor determines a coherence between portions of the brainwaves, typically in the frequency domain, and compares the coherence values, which change rapidly from moment to moment, to thresholds. Based on the comparison of the coherence value to the thresholds, which are adjusted over time based on feedback relating to success, a control signal is developed that can be sent to a real object to control 3 dimensional motion of the control object.

Methods of treating a brain malfunction include obtaining a subject diagnosed with a brain malfunction and reducing EEG frequency of brainwaves in the subject by applying at least one EEG-slowing stimulus to the subject, whereby production of β-amyloid protein in the brain of the subject is reduced and progression of the brain malfunction is halted or slowed.

A method and system for instructing a user behavior change comprising: collecting a first and a second bioelectrical signal dataset; generating an analysis based upon the first and the second bioelectrical signal datasets; and providing a behavior change suggestion to the user based upon the analysis. The method can further comprise collecting a third bioelectrical signal dataset associated with a performance of an action by the user in response to the behavior change suggestion; generating an adherence metric based upon the third bioelectrical signal dataset and at least one of the first and the second bioelectrical signal datasets; providing a stimulus configured to prompt an action by the user; and providing at least one of the analysis and an analysis based upon the adherence metric to the user. An embodiment of the system comprises a biosignal detector and a processor configured to implement an embodiment of the method.

By using an iterative loop of data collection, binaural tone generation/presentation, and analysis binaural tones can be introduced to induce an existing brain state to change from one associated with being awake to a state associated with being asleep. The current state of an individual's brain is determined by measuring movement and electrical activity. Using this data a binaural tone can be generated to induce the brain state to change. As the state of the brain is continually monitored the applied binaural tone is modified and applied until the desired sleep state is obtained.

Trigeminal nerves are stimulated based upon pulse counting and chronobiology. A cutaneous electrode assembly is applied to the forehead to stimulate the ophthalmic nerves. A method may include determining a number of pulses to be administered to a patient based upon the disorder being treated, and pulsing current through an electrode assembly to stimulate the patient's supraorbital and supratrochlear nerves with the determined number of pulses. Another method may include determining a pulse repetition frequency for pulses to be administered to a patient based upon the disorder being treated, and pulsing current through an electrode assembly to stimulate the patient's supraorbital and supratrochlear nerves at the pulse repetition frequency.

Neurofeedback training executed by a brain activity training apparatus for performing a training to change the correlation of connectivity between brain areas utilizing correlation of measured connectivity between brain areas involves repetition of a plurality of trials. Each trial includes a resting period T.sub.rest, a self-regulation period T.sub.NF and a presenting period T.sub.Score presenting feedback information. The brain activity training apparatus calculates, from signals detected from a trainee in the resting period by a brain activity detecting device, a baseline level of degrees of activity of prescribed regions corresponding to the functional connectivity as the object of training, calculates, from signals detected in the self-regulation period and from the baseline level, time correlation of degrees of activity of the prescribed regions corresponding to the functional connectivity as the object of training, and calculates information to be fedback.

Described is a system for biofeedback, the system including one or more processors and a memory, the memory being a non-transitory computer-readable medium having executable instructions encoded thereon, such that upon execution of the instructions, the one or more processors perform operations including using a first biometric sensor during performance of a current task, acquiring first biometric data, and producing a first biometric value by assessing the first biometric data. The one or more processors further perform operations including determining a first relevance based on a first significance of a first correlation between the first biometric value and the current task, and controlling a device based on the first relevance and the first biometric value.

The present invention discloses a brain-computer interface method and system based on real-time closed loop vibration stimulation enhancement. The method includes: displaying and providing a motor imagery task to a subject, and collecting a generated digital electroencephalogram signal; reading the digital electroencephalogram signal, judging whether a preset time period is exceeded or not, performing interception if YES, and performing continuous reading if NO; performing band-pass filtering, obtaining time-frequency characteristics of the digital electroencephalogram signal through calculation by fast Fourier transform, and extracting a frequency value with highest frequency energy as a main frequency; obtaining an instantaneous phase of the digital electroencephalogram signal through calculation by Hilbert transform; generating predicted sine waves by respectively using the main frequency and the instantaneous phase as a frequency and an initial phase of sine waves, and predicting and obtaining real-time phase information; and judging whether the real-time phase is in a vibration stimulation application phase interval or not, generating and outputting a control instruction, and controlling a vibration motor to vibrate and to stimulate a sensory channel of the subject according to the control instruction. The present invention improves a signal-to-noise ratio of a brain-computer interface system, and enhances a recognition rate of a motor imagery signal.