Single Trial Classification of EEG and Peripheral Physiological Signals for Recognition of Emotions Induced by Music Videos


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Koelstra, S. and Yazdani, A. and Soleymani, M. and Mühl, Christian and Lee, J.-L. and Nijholt, Anton and Pun, T. and Ebrahimi, T. and Patras, I. (2010) Single Trial Classification of EEG and Peripheral Physiological Signals for Recognition of Emotions Induced by Music Videos. In: Proceedings 2010 International Conference on Brain Informatics (BI 2010), 28-30 August, Toronto (pp. pp. 89-100).

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Abstract:Recently, the field of automatic recognition of users' affective states has gained a great deal of attention. Automatic, implicit recognition of affective states has many applications, ranging from personalized content recommendation to automatic tutoring systems. In this work, we present some promising results of our research in classification of emotions induced by watching music videos. We show robust correlations between users' self-assessments of arousal and valence and the frequency powers of their EEG activity. We present methods for single trial classification using both EEG and peripheral physiological signals. For EEG, an average (maximum) classification rate of 55.7% (67.0%) for arousal and 58.8% (76.0%) for valence was obtained. For peripheral physiological signals, the results were 58.9% (85.5%) for arousal and 54.2% (78.5%) for valence.
Item Type:Conference or Workshop Item
Copyright:© Springer
Faculty:
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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Link to this item:http://purl.utwente.nl/publications/73064
Official URL:http://dx.doi.org/10.1007/978-3-642-15314-3_9
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