Application of Binary Cuckoo Algorithm Based on Rough Set in Emotion Recognition

In order to improve the ability of selecting the best subset of emotion features in emotion recognition, a rough set binary cuckoo algorithm is proposed. The original features of four physiological signals which are galvanic skin reaction, respiratory, electromyography, electroencephalogram are extracted; then, the rough set binary cuckoo algorithm is used to optimize the feature selection, and the support vector machine is used to classify the emotions. Simulation results show that the proposed algorithm can optimize the feature selection process and achieve higher recognition rate with fewer features. It also shows that the emotion recognition effect of multimodal physiological signals is better than that of single modality physiological signal.