Emotion Investigation Based on Biosignals
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.
Keywordsemotional states TESPAR DZ biosignals feature selection SVM
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