Analysis physiological signals for emotion recognition

The emotion recognition is one of the great challenges in human-human and human-computer interaction. In this paper, an approach for the emotions recognition based on physiological signals is proposed. Six basic emotions: joy, sadness, fear, disgust, neutrality and amusement are analysed using physiological signals. These emotions are induced through the presentation of IAPS pictures (International Affecting Picture System) to the subjects. Also, the physiological signals of interest in this analysis are: electromyogram signal (EMG), respiratory volume (RV), skin temperature (SKT), skin conductance (SKC), blood volume pulse (BVP) and heart rate (HR). These are selected to extract some characteristic parameters, which will be used for classifying the emotions. The SVM (support vector machines) technique is used for classifying these parameters. The experimental results show that the proposed methodology provides a recognition rate of 85% for different emotional states.