• DocumentCode
    2598119
  • Title

    Physiology and HRI: Recognition of over- and underchallenge

  • Author

    Wendt, Cornelia ; Popp, Michael ; Karg, Michelle ; Kuhnlenz, Kolja

  • Author_Institution
    Human Factors Inst., Univ. der Bundeswehr Munchen, Munich
  • fYear
    2008
  • fDate
    1-3 Aug. 2008
  • Firstpage
    448
  • Lastpage
    452
  • Abstract
    Contrary to common emotion recognition techniques by face or speech analysis, physiological data are involuntary and continuously available. Thus, they allow for emotion detection even in situations without spoken words or in case of non-extreme emotions, which are more likely to occur in human-robot interaction (HRI). In this paper, we describe the results of an experiment investigating non-extreme emotional states relevant for HRI scenarios (over- and underchallenge). Those states occurred naturally during the course of a LEGO construction task by manipulating working speed. Data collected from 28 subjects were analyzed and the results of different types of discriminant analysis and nearest neighbour methods were compared. Based on two physiological modalities (HR, SCR), correct classification rates of up to 76% for seven features and 74% for only two features were achieved. Overchallenge could be discriminated very well from the other two conditions (96.4 - 85.7%), whereas underchallenge is often confused with the intermediate condition with normal working speed.
  • Keywords
    emotion recognition; intelligent robots; man-machine systems; emotion recognition techniques; face analysis; human-robot interaction; nearest neighbour methods; physiology; speech analysis; Automatic speech recognition; Data engineering; Emotion recognition; Face recognition; Human factors; Human robot interaction; Physiology; Robotics and automation; Skin; Speech analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robot and Human Interactive Communication, 2008. RO-MAN 2008. The 17th IEEE International Symposium on
  • Conference_Location
    Munich
  • Print_ISBN
    978-1-4244-2212-8
  • Electronic_ISBN
    978-1-4244-2213-5
  • Type

    conf

  • DOI
    10.1109/ROMAN.2008.4600707
  • Filename
    4600707