Comparison of Emotion Recognition Methods from Bio-Potential Signals

• TAKAHASHI Kazuhiko

  Yamaguchi University currently Doshisha University

抄録

This paper proposes an emotion recognition system from multi-modal bio-potential signals. For emotion recognition, two types of classifier: neural network (NN) and support vector machine (SVM) are designed and investigated. Using gathered data under psychological emotion stimulation experiments, the classifiers are trained and tested. In computational experiments of recognizing two emotions: pleasure and displeasure, recognition rates of 62.3% with the NN classifier and 59.7% with the SVM classifier are achieved. The experimental result shows that using multi-modal bio-potential signals is feasible and that NN is comparably more suited for emotion recognition tasks.

収録刊行物

• 人間工学

  人間工学 40 (2), 90-98, 2004

  一般社団法人 日本人間工学会

キーワード

• Emotion
• Brain wave
• Heart rate
• Pulse
• Neural network
• Support vector machine

詳細情報

• CRID: 1390001204537560704
• NII論文ID: 130003872840
• NII論文ID: 10012846272
• NII書誌ID: AN00199371
• DOI: 10.5100/jje.40.90
• ISSN: 18842844
• ISSN: 05494974
• NDL書誌ID: 6921671
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I6921671
• 本文言語コード: en
• データソース種別:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可