Stress Emotion Recognition Based on RSP and EMG Signals

Abstract

To recognize the stress emotion, a subject was put alternately in periods of high and low stress by configuring the speed and difficulty of a game named Tetris. The respiration (RSP) signal and the electromyogram (EMG) signal with different stress level were then acquired. After preprocessing, the mathematical features were calculated and automatic detection of stress level based on Fisher linear discriminant classifier was realized. The results show that the average correct detection rate of stress level based on the EMG signal can reach 97.8%. That of the RSP signal is only 86.7%. The EMG signal is more effective than the RSP signal in detection of stress level. Union of multiple physiological signals can effectively improve the correct detection rate.