The present invention discloses a method for determining a degree of response to a physical activity. Acquire a physical activity signal measured by a sensing unit in the physical activity. Determine first data of a first physical activity feature set based on the physical activity signal. Determine a recognition of the degree of response to the physical activity based on the first data of the first physical activity feature set by a mathematical model describing a relationship between the first physical activity feature set and the degree of response to a physical activity. A portion of a first mechanism of the mathematical model adopts at least one portion of a second mechanism of a first neural network model associated with the second physical activity feature set.

The present application discloses a method for eliminating multi-channel gain errors of an EEG signal acquisition system. The system includes an acquisition electrode, decoupling input capacitors, input units, intra-channel chopper modulators, inter-channel chopper modulators, fully differential closed-loop amplifiers, inter-channel chopper demodulators, intra-channel chopper demodulators, low-pass filters and an output unit sequentially arranged in a signal flow direction of channels. The method includes a process of intra-channel chopping modulation, multi-level inter-channel chopping modulation, amplification, multi-level inter-channel chopping demodulation, intra-channel chopping demodulation, and low-pass filtering. The present application eliminates gain errors between channels, ensures signal acquisition accuracy, and avoids flicker noise in amplifiers.

The present application discloses a method for eliminating multi-channel gain errors of an EEG signal acquisition system. The system includes an acquisition electrode, decoupling input capacitors, input units, intra-channel chopper modulators, inter-channel chopper modulators, fully differential closed-loop amplifiers, inter-channel chopper demodulators, intra-channel chopper demodulators, low-pass filters and an output unit sequentially arranged in a signal flow direction of channels. The method includes a process of intra-channel chopping modulation, multi-level inter-channel chopping modulation, amplification, multi-level inter-channel chopping demodulation, intra-channel chopping demodulation, and low-pass filtering. The present application eliminates gain errors between channels, ensures signal acquisition accuracy, and avoids flicker noise in amplifiers.

A method for functional brain mapping using high gamma modulation obtained from stereoelectroencephalography (SEEG).

A method for functional brain mapping using high gamma modulation obtained from stereoelectroencephalography (SEEG).

A device for determining a physiological or psychological state of a mammal is disclosed. The device has at least one earpiece with a main body having a body of revolution with an axis of revolution, and an endpiece configured to be inserted into an ear canal. The endpiece has a cylindrical channel intended to receive a body of revolution for detachably mounting the endpiece on the main body, the endpiece being arranged to be movable in rotation about the axis of revolution in order to allow at least one electrode to be oriented toward a zone of the brain of the mammal, and the endpiece having a plurality of electrodes arranged on an outer surface of the endpiece, each electrode being configured to pick up an electrical signal in the ear canal of the mammal.

A device for determining a physiological or psychological state of a mammal is disclosed. The device has at least one earpiece with a main body having a body of revolution with an axis of revolution, and an endpiece configured to be inserted into an ear canal. The endpiece has a cylindrical channel intended to receive a body of revolution for detachably mounting the endpiece on the main body, the endpiece being arranged to be movable in rotation about the axis of revolution in order to allow at least one electrode to be oriented toward a zone of the brain of the mammal, and the endpiece having a plurality of electrodes arranged on an outer surface of the endpiece, each electrode being configured to pick up an electrical signal in the ear canal of the mammal.

[Object] Proposed are a biopotential measuring apparatus, a biopotential measuring system, and a biopotential measuring method that are capable of suppressing an erroneous determination in determining the quality of a contact state between an electrode and a living body. A biopotential measuring apparatus of the present technology includes an electrode and a controller. The electrode measures a biopotential. The controller determines a quality of a contact state between the electrode and a living body on the basis of a signal amplitude of a signal of a specific frequency.

In one aspect of the present disclosure, method includes: receiving neural data responsive to a listener's auditory attention; receiving an acoustic signal responsive to a plurality of acoustic sources; for each of the plurality of acoustic sources: generating, from the received acoustic signal, audio data comprising one or more features of the acoustic source, forming combined data representative of the neural data and the audio data, and providing the combined data to a classification network configured to calculate a similarity score between the neural data and the acoustic source using one or more similarity metrics; and using the similarity scores calculated for each of the acoustic sources to identify, from the plurality of acoustic sources, an acoustic source associated with the listener's auditory attention.

In one aspect of the present disclosure, method includes: receiving neural data responsive to a listener's auditory attention; receiving an acoustic signal responsive to a plurality of acoustic sources; for each of the plurality of acoustic sources: generating, from the received acoustic signal, audio data comprising one or more features of the acoustic source, forming combined data representative of the neural data and the audio data, and providing the combined data to a classification network configured to calculate a similarity score between the neural data and the acoustic source using one or more similarity metrics; and using the similarity scores calculated for each of the acoustic sources to identify, from the plurality of acoustic sources, an acoustic source associated with the listener's auditory attention.