Comparing Two Emotion Models for Deriving Affective States from Physiological Data

  • Antje Lichtenstein
  • Astrid Oehme
  • Stefan Kupschick
  • Thomas Jürgensohn
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4868)


This paper describes an experiment on emotion measurement and classification based on different physiological parameters, which was conducted in the context of a European project on ambient intelligent mobile devices. Emotion induction material consisted of five four-minute video films that induced two positive and three negative emotions. The experimental design gave consideration to both, the basic and the dimensional model of the structure of emotion. Statistical analyses were conducted for films and for self-assessed emotional state and in addition, supervised machine learning technique was utilized. Recognition rates reached up to 72% for a specific emotion (one out of five) and up to 82% for an underlying dimension (one out of two).


Emotion classification dimensional model of affect basic emotions ambient intelligence psychophysiology 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Antje Lichtenstein
    • 1
  • Astrid Oehme
    • 2
  • Stefan Kupschick
    • 2
  • Thomas Jürgensohn
    • 2
  1. 1.Institut für Psychologie und ArbeitswissenschaftTechnische Universität BerlinBerlinGermany
  2. 2.HFC Human-Factors-Consult GmbHBerlinGermany

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