Emotion recognition method of multi-channel electroencephalogram (EEG) data and electronic device

Abstract

The invention discloses an emotion recognition method of multi-channel electroencephalogram (EEG) data and an electronic device. The method includes the steps: sending frequency domain features of channels of extracted EEG data into a sequence feature extractor so as to obtain hidden-layer feature vectors of the channels of the EEG data, capturing association between the EEG channels and emotion categories, and sending the association and the hidden-layer feature vectors to an automatic encoder so as to obtain probability value vectors of the emotion category corresponding to the EEG data. Long-term and short-term memory networks are utilized to learn the non-linear relationship between the EEG channels on the EEG channel sequence, the high-dimensional EEG features related to the emotion categories are extracted, the key information in the multi-channel EEG signals are selected automatically, and EEG feature field differences which are caused by instability of the EEG data and environmental change are reduced.

Description

technical field [0001] The invention belongs to the field of emotion recognition, and in particular relates to an emotion recognition method and electronic device of multi-channel EEG data. Background technique [0002] Human emotions are complex psychological and physiological expressions often associated with subjective feelings, temperament, personality, motivational dispositions, behavioral responses, and physiological arousal. In the field of emotion recognition research, both human behavior and physiological signals are widely used in human emotion recognition. Physiological signals such as electroencephalogram (EEG), electromyography (EMG), and electrocardiogram (ECG) are more reliable for identifying human emotions than behavioral signals such as language, facial expressions, gestures, and body movements that tend to mask human emotions. and true. EEG signal is a physical signal with good time resolution, which can be directly used for emotion recognition by analyz...

AI Technical Summary

Problems solved by technology

However, this method still cannot automatically select the key information in the multi-channel EEG signal, and does not solve the difference between the source data feature distribution and the target data feature distribution

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