Title :
Remarks on emotion recognition from multi-modal bio-potential signals
Author :
Takahashi, Kazuhiko
Author_Institution :
Doshisha Univ., Kyoto, Japan
Abstract :
This paper proposes an emotion recognition system from multi-modal bio-potential signals. For emotion recognition, support vector machines (SVM) are applied to design the emotion classifier and its characteristics are investigated. Using gathered data under psychological emotion stimulation experiments, the classifier is trained and tested. In experiments of recognizing five emotion: joy, anger, sadness, fear, and relax, recognition rate of 41.7% is achieved. The experimental result shows that using multi-modal bio-potential signals is feasible and that SVM is well suited for emotion recognition tasks.
Keywords :
emotion recognition; medical signal processing; neural nets; physiological models; psychology; support vector machines; SVM; emotion classifier; emotion recognition; multimodal biopotential signals; multimodal sensors; support vector machines; Artificial neural networks; Electroencephalography; Emotion recognition; Face recognition; Humans; Skin; Speech recognition; Support vector machine classification; Support vector machines; Testing;
Conference_Titel :
Industrial Technology, 2004. IEEE ICIT '04. 2004 IEEE International Conference on
Print_ISBN :
0-7803-8662-0
DOI :
10.1109/ICIT.2004.1490720