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Four-Channel Biosignal Analysis and Feature Extraction for Automatic Emotion Recognition

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Biomedical Engineering Systems and Technologies (BIOSTEC 2008)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 25))

Abstract

This paper investigates the potential of physiological signals as a reliable channel for automatic recognition of user’s emotial state. For the emotion recognition, little attention has been paid so far to physiological signals compared to audio-visual emotion channels such as facial expression or speech. All essential stages of automatic recognition system using biosignals are discussed, from recording physiological dataset up to feature-based multiclass classification. Four-channel biosensors are used to measure electromyogram, electrocardiogram, skin conductivity and respiration changes. A wide range of physiological features from various analysis domains, including time/frequency, entropy, geometric analysis, subband spectra, multiscale entropy, etc., is proposed in order to search the best emotion-relevant features and to correlate them with emotional states. The best features extracted are specified in detail and their effectiveness is proven by emotion recognition results.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, University of Augsburg, Eichleitnerstr. 30, D-86159, Augsburg, Germany

    Jonghwa Kim & Elisabeth André

Authors
  1. Jonghwa Kim
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  2. Elisabeth André
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Editor information

Editors and Affiliations

  1. IST - Instituto Superior Técnico, Instituto de Telecomunicaçöes, Av. Rovisco Pais, 1, 1049-001, Lisbon, Portugal

    Ana Fred

  2. Polytechnic Institute of Setúbal – INSTICC, Departament of Systems and Informatics, Rua do Vale de Chaves - Estefanilha, 2910-761, Setúbal, Portugal

    Joaquim Filipe

  3. Institute of Telecommunications, Av. Rovisco Pais, 1, 1049-001, Lisboa, Portugal

    Hugo Gamboa

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© 2008 Springer-Verlag Berlin Heidelberg

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Kim, J., André, E. (2008). Four-Channel Biosignal Analysis and Feature Extraction for Automatic Emotion Recognition. In: Fred, A., Filipe, J., Gamboa, H. (eds) Biomedical Engineering Systems and Technologies. BIOSTEC 2008. Communications in Computer and Information Science, vol 25. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92219-3_20

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  • DOI: https://doi.org/10.1007/978-3-540-92219-3_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-92218-6

  • Online ISBN: 978-3-540-92219-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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