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Automatic Recognition of the Unconscious Reactions from Physiological Signals

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Human Factors in Computing and Informatics (SouthCHI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 7946))

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Abstract

While the research in affective computing has been exclusively dealing with the recognition of explicit affective and cognitive states, carefully designed psychological and neuroimaging studies indicated that a considerable part of human experiences is tied to a deeper level of a psyche and not available for conscious awareness. Nevertheless, the unconscious processes of the mind greatly influence individuals’ feelings and shape their behaviors. This paper presents an approach for automatic recognition of the unconscious experiences from physiological data. In our study we focused on primary or archetypal unconscious experiences. The subjects were stimulated with the film clips corresponding to 8 archetypal experiences. Their physiological signals including cardiovascular, electrodermal, respiratory activities, and skin temperature were monitored. The statistical analysis indicated that the induced experiences could be differentiated based on the physiological activations. Finally, a prediction model, which recognized the induced states with an accuracy of 79.5%, was constructed.

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Author information

Authors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, The Netherlands

    Leonid Ivonin, Huang-Ming Chang, Wei Chen & Matthias Rauterberg

Authors
  1. Leonid Ivonin
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  2. Huang-Ming Chang
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  3. Wei Chen
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  4. Matthias Rauterberg
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Editor information

Editors and Affiliations

  1. Institute for Medical Informatics, Statistics and Documentation (IMI), Medical University Graz, Auenbruggerplatz 2/V, 8036, Graz, Austria

    Andreas Holzinger

  2. Human-Computer Interaction Center, RWTH Aachen University, Theaterplatz 14, 52056, Aachen, Germany

    Martina Ziefle

  3. Institute of Informatics Systems, Alpen-Adria Universität Klagenfurt, Universitätsstrasse 65-67, 9020, Klagenfurt, Austria

    Martin Hitz

  4. Faculty of Electrical and Computer Engineering, University of Maribor, Smetanova 17, 2000, Maribor, Slovenia

    Matjaž Debevc

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Ivonin, L., Chang, HM., Chen, W., Rauterberg, M. (2013). Automatic Recognition of the Unconscious Reactions from Physiological Signals. In: Holzinger, A., Ziefle, M., Hitz, M., Debevc, M. (eds) Human Factors in Computing and Informatics. SouthCHI 2013. Lecture Notes in Computer Science, vol 7946. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39062-3_2

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  • DOI: https://doi.org/10.1007/978-3-642-39062-3_2

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