Automatic recognition of the unconscious reactions from physiological signals

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

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

6 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Subtitle of host publicationFirst International Conference, SouthCHI 2013
Pages16-35
Number of pages20
Volume7946 LNCS
DOIs
Publication statusPublished - 2013
Event1st International Conference on Human Factors in Computing and Informatics, SouthCHI 2013 - Maribor, Slovenia
Duration: 1 Jul 20133 Jul 2013

Conference

Conference1st International Conference on Human Factors in Computing and Informatics, SouthCHI 2013
CountrySlovenia
CityMaribor
Period1/07/133/07/13

Keywords

  • Affective computing
  • archetypes
  • the collective unconscious

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    Ivonin, L., Chang, H. M., Chen, W., & Rauterberg, M. (2013). Automatic recognition of the unconscious reactions from physiological signals. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): First International Conference, SouthCHI 2013 (Vol. 7946 LNCS, pp. 16-35) https://doi.org/10.1007/978-3-642-39062-3_2