• DocumentCode
    178939
  • Title

    Automatic Pain Recognition from Video and Biomedical Signals

  • Author

    Werner, P. ; Al-Hamadi, A. ; Niese, R. ; Walter, S. ; Gruss, S. ; Traue, H.C.

  • Author_Institution
    Inst. for Inf. Technol. & Commun., Univ. of Magdeburg, Magdeburg, Germany
  • fYear
    2014
  • fDate
    24-28 Aug. 2014
  • Firstpage
    4582
  • Lastpage
    4587
  • Abstract
    How much does it hurt? Accurate assessment of pain is very important for selecting the right treatment, however current methods are not sufficiently valid and reliable in many cases. Automatic pain monitoring may help by providing an objective and continuous assessment. In this paper we propose an automatic pain recognition system combining information from video and biomedical signals, namely facial expression, head movement, galvanic skin response, electromyography and electrocardiogram. Using the BioVid Heat Pain Database, the system is evaluated in the task of pain detection showing significant improvement over the current state of the art. Further, we discuss the relevance of the modalities and compare person-specific and generic classification models.
  • Keywords
    biomechanics; electrocardiography; electromyography; face recognition; image classification; medical image processing; skin; BioVid Heat Pain Database; automatic pain recognition system; biomedical signals; electrocardiogram; electromyography; facial expression; galvanic skin response; generic classification models; head movement; pain detection; person-specific models; video signals; Data integration; Databases; Electromyography; Feature extraction; Head; Pain; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2014 22nd International Conference on
  • Conference_Location
    Stockholm
  • ISSN
    1051-4651
  • Type

    conf

  • DOI
    10.1109/ICPR.2014.784
  • Filename
    6977497