• 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