Real-Time Emotional State Estimator for Adaptive Virtual Reality Stimulation

Authors:
Davor Kukolja;Siniša Popović;Branimir Dropuljić;Marko Horvat;Krešimir Ćosić
Affiliations:
Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia 10000;Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia 10000;Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia 10000;Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia 10000;Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia 10000
Venue:
FAC '09 Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009
Year:
2009

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Abstract

The paper presents design and evaluation of emotional state estimator based on artificial neural networks for physiology-driven adaptive virtual reality (VR) stimulation. Real-time emotional state estimation from physiological signals enables adapting the stimulations to the emotional response of each individual. Estimation is first evaluated on artificial subjects, which are convenient during software development and testing of physiology-driven adaptive VR stimulation. Artificial subjects are implemented in the form of parameterized skin conductance and heart rate generators that respond to emotional inputs. Emotional inputs are a temporal sequence of valence/arousal annotations, which quantitatively express emotion along unpleasant-pleasant and calm-aroused axes. Preliminary evaluation of emotional state estimation is also performed with a limited set of humans. Human physiological signals are acquired during simultaneous presentation of static pictures and sounds from valence/arousal-annotated International Affective Picture System and International Affective Digitized Sounds databases.