Research on EEG signal recognition based on channel selection

Emotional recognition as the key technology in the field of emotion computing has received more and more attentions in applications such as human-computer interaction, medical-assisted diagnosis and multimedia intelligence recommendation, and it has important research and application value. EEG recognition based on EEG is a commonly used and effective method of emotion recognition. More and more scholars are concerned with the emotional recognition of specific brain regions and specific frequency bands in the study of emotion recognition based on EEG. They will be based on the distance between the brain electrode and the principle of symmetry divided into different regions to extract EEG characteristics, follow-up identification study. But this way ignores the emotional correlation and difference between the channels, which in turn affects the EEG feature representation and recognition effect. In this paper, we propose a channel selection method based on the maximum correlation minimum redundancy idea, and then it obtains 10 ideal channels for the futher EEG emotional analysis.