Emotion feature selection from physiological signal based on BPSO

In emotion recognition, many irrelevant and redundant features will affect recognition results, so feature selection is necessary. Aimed at emotion physiological signal feature selection, this paper proposed with improved discrete binary particle swarm optimization(BPSO) to increase the correct classification rate of emotion state. When recognizing four emotional states with nearest classifier by four physiological signals, the whole correct recognition rate is up to 85%. Experimental results demonstrate that the BPSO is an effective way to emotion physiological signals feature selection.