Recognizing the Effects of Voluntary Facial Activations Using Heart Rate Patterns

Continuously measured physiological signals have the potential to act as non-invasive, real time indicators of human psychophysiological phenomena. Recently, several non-intrusive, wireless, and discrete measurement devices have been developed. For these reasons, there has been growing interest for using physiological signals for estimating emotions and other psychological processes during human-computer interaction. In the current work, we present the first steps towards constructing a person-independent online system that automatically identifies heart rate responses and estimates subjective experiences during voluntary facial activations. The preliminary results of our study showed that voluntarily produced facial expressions had an effect on subjective emotional experiences and physiological processes. Further, our results suggest that heart rate responses to facial activations can be detected and classified in order to support more accurate and efficient emotion detection. Key-Words: Affective computing, emotion recognition, heart rate patterns, pattern classification, psychophysiology, biosignal processing, voluntary facial activations.