An apparatus for measuring brain cell activity in artificial blood circulation according to an embodiment of the present invention may include a measuring unit (10) that measures EEG signals; an analog-to-digital converter (ADC) 20 that converts the EEG signals measured at the measuring unit 10 into digital signals; a control unit 50 that calculates EEG parameters from the digital EEG signals converted at the ADC 20, and calculates end-tidal carbon dioxide tension and cerebral blood flow from the EEG parameters.

Systems, methods, and products for language learning that may extract text from various resources having text, using various natural-language processing features, which can be combined with custom-designed learning activities to offer a needs-based, adaptive learning methodology. The system may receive a resource, extract keywords pedagogically valuable to non-native language learning and academic exercises. Metadata describing various aspects of resources from which keywords are extracted may be associated with keywords. Metadata describing various aspects of keywords may also be associated with keywords. Extracted keywords may be stored into a keyword store along with any metadata associated with keywords.

This disclosure relates generally to stress classification and quantification, and more particularly to system and method for classification and quantitative estimation of cognitive stress from analysis of keystrokes and signals derived from physiological sensors. In one embodiment, a method includes obtaining, while a user is engaged in performance of a task, physiological signals from physiological sensors accessible to the user. Feature sets are identified from the physiological signals which correlate with cognitive stress experienced by the user. Using a regression model, a stress indicator metric comprising a quantitative estimate of the cognitive stress is predicted. The regression model is trained using the feature sets and independently determined quantitative estimates of cognitive stress used as a ground truth to output the value of the stress indicator metric. The ground truth is determined from keystroke data associated with the performance of keyboard-based tasks comprising navigation of moving objects to the target.

The present invention relates to a system (10) for supporting an elderly, frail and/or diseased person (12), in particular a person suffering from Parkinson's disease, wherein the system (10) comprises: a detection unit (14) including (i) a brain activity sensor (20) for detecting a brain activity signal relating to the brain activity of the person (12) and (ii) a motion detection unit (22) for detecting a motion signal relating to a motion of one or more body parts of the person (12); an analysis unit (16) for determining, based on the detected brain activity signal and motion signal, an activity level of the person (12) which is indicative of the motoric and cognitive activity of the person (12); and a feedback unit (18) for providing a feedback to the person (12) if the activity level of the person (12) exceeds a predetermined threshold.

The present invention relates to a method for generating a sensorial stimulus using electroencephalographic data acquired from a subject, the method comprising the following steps: receiving electroencephalographic data comprising at least two electroencephalographic signals measured simultaneously from at least two electroencephalogram channels; calculating an alpha phase neuromarker on consecutive epochs of the electroencephalographic data, the alpha phase neuromarker being representative of at least the phase coherence between alpha waves recorded from the at least two electroencephalogram channels; and generating a sensorial stimulus representing alpha phase neuromarker using an output generator.

The present invention discloses a brain activity analysis method and apparatus, which is based on a nonlinear waveform decomposition technology, wherein the changes of the intrinsic features in brain waves are decomposed and demodulated to extract the modulation signals of the components, including the frequency-modulation signals and the amplitude-modulation signals. The present invention further uses a feature mask to determine whether to proceed further decomposition and demodulation of the extracted modulation signals. If not, the multidimensional changes of the intrinsic features are obtained according to the feature mask. Then, quantitation and identification is performed to obtain the status of brain function. The present invention not only effectively increases the accuracy of the identification but also uses the feature mask to obviously reduce the complexity and the load of computation.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for presenting a human participant with information known to stimulate a person's neural reward system. Receiving an EEG signal from a sensor coupled to the human participant in response to presenting the participant with the information, the EEG signal being associated with the participant's neural reward system. Contemporaneously with receiving the EEG signal, receiving contextual information related to the information presented to the human participant. Processing the EEG signal and the contextual information in real time using a machine learning model trained to associate depression in the person with EEG signals associated with the person's neural reward system and the presented information. Diagnosing whether the participant is experiencing depression based on an output of the machine learning model.

The present invention relates to a device for detecting a state of true perception loss of a human, the device including processing means operable to detect from information on electrical signals sensed adjacent to the scalp of the human the activity of oscillations present in the electrical signals as a marker for the state of true perception loss of the human.

An exemplary embodiment providing one or more improvements includes apparatus and methods for sensing electrical activity in tissue of a person in a manner which is substantially limits or eliminates interference from noise in a surrounding environment.

Systems and method for age-compensated monitoring of a patient experiencing administration of at least one drug having anesthetic properties are provided. In one embodiment, a system includes a plurality of sensors configured to acquire physiological data from the patient and at least one processor configured to receive the physiological data from the plurality of sensors, and determine, from the physiological data, signal markers indicative of an apparent or likely patient age. The at least one processor is also configured to at least one of scale and regulate the physiological data using at least the apparent patient age to create age-compensated data, and generate a report including the age-compensated data.