A more practical method for evaluating an inhibitory circuit applicable to a living body, and the use thereof. Herein the action of an inhibitory circuit on an excitatory circuit is evaluated on the basis of attenuation of the brain activity produced by activation of an excitatory circuit by the input of an inhibitory circuit by performing a step for inputting an inhibitory circuit by applying a second trigger in advance of a first trigger to an excitatory circuit activated by a first trigger which is a stimulus or challenge.

Brain modelling includes receiving time-coded bio-signal data associated with a user; receiving time-coded stimulus event data; projecting the time-coded bio-signal data into a lower dimensioned feature space; extracting features from the lower dimensioned feature space that correspond to time codes of the time-coded stimulus event data to identify a brain response; generating a training data set for the brain response using the features; training a brain model using the training set, the brain model unique to the user; generating a brain state prediction for the user output from the trained brain model, and automatically computing similarity metrics of the brain model as compared to other user data; and inputting the brain state prediction to a feedback model to determine a feedback stimulus for the user, wherein the feedback model is associated with a target brain state.

The present method and system provides for the clinical application of neurostimulation and/or neuromodulation to a patient. The method and system includes receipt and acquisition of patient data, processing of that data relative to one or more known data sets, and determination of a good-fit trigger specific treatment protocol. The method and system provides for application of the protocol to the patient, including delivery of neuromodulation and biofeedback. Based thereon, the method and system re-iterates the goodness of fit determination for further treatment to the patient.

Systems and methods are disclosed for management of anesthetized patients. The systems and methods can enable determination of whether the patient risks an anesthetic complication, an intraoperative stroke, or awareness during anesthesia. The disclosed systems and methods can involve receiving a signal from EEG electrodes on the head of a patient during presentation of a stimuli to the patient. This signal can be used to generate segment posteriorization index values and/or synchronization values. Based on synchronization values anesthesia depth of the patient can be reduced or a surgical intervention performed. Based on segment posteriorization index values anesthesia depth of the patient can be increased.

A medical device may receive sensor data from sensing sources, and determine confidence levels for sensor data received from each of the plurality of sensing sources. Each of the confidence levels of the sensor data from each of the sensing sources is a measure of accuracy of the sensor data received from respective sensing sources. The medical device may also determine one or more therapy parameter values based on the determined confidence levels, and cause delivery of therapy based on the determined one or more therapy parameter values.

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.

Brain activity of a user is detected, and a mental state of the user is determined. In one technique, life/work context is automatically presented to the user in a manner that modulates the mental state of the user. In another technique, an entertainment selection is presented to the user, and an entertainment selection list is automatically modified in response to the determined mental state of the user. In still another technique, the mental state that is determined is a negative emotional state, and life/work context is automatically presented to the user in a manner that promotes a cognitive state of the user in response to the determined emotional state of the user. In yet another technique, the wellness of the user is automatically tracked over a time period based on the determined mental state.

A bioelectrical signal controlled exercise machine system for allowing an exerciser to control the state of an exercise machine and exercise environment. The bioelectrical signal controlled exercise machine system generally includes an exercise machine, a bioelectrical sensor device and a control unit in communication with the bioelectrical sensor device and the exercise machine. The control unit is adapted to receive data from the bioelectrical sensor device relating to measured bioelectrical signals of the human exerciser, and wherein the control unit transmits a control signal to the exercise machine to change the state of the exercise machine based on the data from the bioelectrical sensor device.

A portable apparatus and a method of changing a content screen of the portable apparatus are provided. The portable apparatus includes changing a displayed content in response to an increase in a visual fatigue and a method of changing a content screen of the portable apparatus. Some of disclosed various embodiments provide a portable apparatus that calculates a visual fatigue by using user electroencephalogram (EEG) information received from a wearable apparatus and changing a displayed content into another content in response to an increase in the calculated visual fatigue, and a method of changing a content screen of the portable apparatus.

Provided in the embodiments of the present disclosure are a control method and device based on brain signal, and a human-machine interaction device, which periodically acquire EEG signals and cerebral oxygen signals within a target period, generate an electroencephalogram (EEG) wave curve representing changes of the EEG signals and a cerebral oxygen wave curve representing changes of the cerebral oxygen signals respectively within the target period, determine whether the EEG wave curve and the cerebral oxygen wave curve satisfy a condition for controlling a controlled device to perform a target operation, and control the controlled device to perform the target operation when the EEG wave curve and the cerebral oxygen wave curve satisfy the condition.