DocumentCode
1605014
Title
Remarks on emotion recognition from multi-modal bio-potential signals
Author
Takahashi, Kazuhiko
Author_Institution
Doshisha Univ., Kyoto, Japan
Volume
3
fYear
2004
Firstpage
1138
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Technology, 2004. IEEE ICIT '04. 2004 IEEE International Conference on
Print_ISBN
0-7803-8662-0
Type
conf
DOI
10.1109/ICIT.2004.1490720
Filename
1490720
Link To Document