Biosignals Analysis and its Application in a Performance Setting - Towards the Development of an Emotional-Imaging Generator

The study of automatic emotional awareness of human subjects by computerized systems is a promising avenue of research in human-computer interaction with profound implications in media arts and theatrical performance. A novel emotion elicitation paradigm focused on self-generated stimuli is applied here for a heightened degree of confidence in collected physiological data. This is coupled with biosignal acquisition (electrocardiogram, blood volume pulse, galvanic skin response, respiration, phalange temperature) for determination of emotional state using signal processing and pattern recognition techniques involving sequential feature selection, Fisher dimensionality reduction and linear discriminant analysis. Discrete emotions significant to Russell’s arousal/valence circumplex are classified with an average recognition rate of 90%.