Bodily Electrodermal Representations for Affective Computing

The view of embodied emotion believes that emotions are the emotions of the body. While emotion-specific patterns of self-reported bodily sensation have been previously reported, the physiological bodily representation across emotions remains to be addressed. The present study aimed to investigate the effectiveness of multi-site bodily electrodermal representations of emotions. A multi-channel electrodermal measurement device was designed to record electrodermal activities from nine body sites (neck, back, chest, bilateral abdomen, bilateral wrist, and bilateral ankle) from thirty-six college students (all male), while they were presented with a series of emotional pictures. Using the integral skin conductance response feature and a random forest classification method, the classification of high and low arousal levels achieved an average classification accuracy of 80.4±8.1%, and the classification of positive, neutral, and negative states reached an average classification accuracy of 76.4±10.2%. The classification models for arousal and valence were found to rely on distinct bodily representations. Meanwhile, the classification results of multi-site measurement were significantly better than single-site results. Our findings for the first time illustrate the bodily electrodermal representations of emotion and suggest the feasibility of affective computing using bodily electrodermal signals.