Emotion recognition method and system based on electroencephalogram signals

Abstract

The invention discloses an emotion recognition method and system based on electroencephalogram signals. The method comprises the following steps: acquiring to-be-identified multi-channel electroencephalogram signals that are electroencephalogram signals from multiple channels when a to-be-identified person watches videos capable of stimulating different emotions; carrying out feature extraction onthe to-be-identified multi-channel electroencephalogram signals based on a discrete wavelet transform algorithm to obtain electroencephalogram features, including frequency band entropies and frequency band energy, of all channels; according to a minimum redundancy maximum correlation algorithm, performing feature selection on the electroencephalogram features to obtain electroencephalogram feature selection signals; and classifying the electroencephalogram feature selection signals by adopting a kernel extreme learning machine algorithm to obtain an electroencephalogram signal emotion recognition result. The emotion recognition precision can be improved.

Description

technical field [0001] The invention relates to the field of emotion recognition, in particular to an emotion recognition method and system based on electroencephalogram signals. Background technique [0002] Human emotion is a comprehensive psychological and physical experience, often accompanied by physiological arousal and certain external manifestations. Studies have shown that 80% of human communication information is emotional information. With the development of human-computer interaction, whether it is on professional, personal or social level, emotion recognition is becoming more and more important, and it is an important part of realizing full interaction between human and machine. [0003] At present, the signals used for emotion recognition are mainly behavioral signals and physiological signals. Among them, behavioral signals include facial expressions, voices, body postures, etc. These signals are external manifestations caused by human emotion stimulation. Ce...

AI Technical Summary

Problems solved by technology

[0007] It can be seen from the above that the selection of EEG channels is particularly critical for the accuracy of emotion recognition when based on EEG signals, and the existing methods rely on experience to select EEG channels or to study the correspondence between emotional states and the entire brain region. It is difficult to select a relatively good EEG channel only for a certain method of channel selection, so the accuracy of the existing EEG channel selection method is low, which will result in low accuracy of emotion recognition

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