Subgroup analysis from psychophysiological signals

This study involves intraand inter-individual emotion classifications from psychophysiological signals and subgroup analysis on the influence of gender and age and their interaction on the emotion recognition. Individual classifications are conducted using a selection of feature optimization, classification and evaluation approaches. The subgroup analysis is based on the inter-individual classification. Emotion elicitation is conducted using standardized pictures in the Valence-Arousal-Dominance dimensions and affective states are classified into five different category classes. Advantageous intra-individual rates are obtained via multi-channel classification and the respiration best contributes to the recognition. High interindividual variances are obtained showing large variability in physiological responses between the subjects. Classification rates are significantly higher for women than for men for the 3-category-class of Valence. Compared to old subjects, young subjects have significantly higher rates for the 3-category-class and 2-category-class of Dominance. Moreover, young men’s classification performed the best among the other subgroups for the 5-category-class of Valence/Arousal.