Abstract
In this paper a physiological signal-based emotion recognition approach is presented. The input bio-signals are electromyogram, electrocardiogram, skin conductivity and respiration change. The feature vector is extracted from each signal type by using the same technique based on wavelets and TESPAR DZ method. A Support Vector Machine (SVM) classifier was employed to distinguish among four emotional states: joy, anger, sadness and pleasure. The database employed in our experiments is the AuBT corpus.
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© 2011 Springer-Verlag Berlin Heidelberg
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Lupu, E., Emerich, S., Arsinte, R. (2011). Emotion Investigation Based on Biosignals. In: Vlad, S., Ciupa, R.V. (eds) International Conference on Advancements of Medicine and Health Care through Technology. IFMBE Proceedings, vol 36. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22586-4_42
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DOI: https://doi.org/10.1007/978-3-642-22586-4_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-22585-7
Online ISBN: 978-3-642-22586-4
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