Abstract
The arousal dimension of human emotions is assessed from two different physiological sources: peripheral signals and electroencephalographic (EEG) signals from the brain. A complete acquisition protocol is presented to build a physiological emotional database for real participants. Arousal assessment is then formulated as a classification problem, with classes corresponding to 2 or 3 degrees of arousal. The performance of 2 classifiers has been evaluated, on peripheral signals, on EEG’s, and on both. Results confirm the possibility of using EEG’s to assess the arousal component of emotion, and the interest of multimodal fusion between EEG’s and peripheral physiological signals.
This work is supported by the European project Similar, http://www.similar.cc. The authors gratefully acknowledge Prof. S. Voloshynovskiy and Dr. T. I. Alecu for many helpful discussions.
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Chanel, G., Kronegg, J., Grandjean, D., Pun, T. (2006). Emotion Assessment: Arousal Evaluation Using EEG’s and Peripheral Physiological Signals. In: Gunsel, B., Jain, A.K., Tekalp, A.M., Sankur, B. (eds) Multimedia Content Representation, Classification and Security. MRCS 2006. Lecture Notes in Computer Science, vol 4105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11848035_70
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DOI: https://doi.org/10.1007/11848035_70
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