• DocumentCode
    624294
  • Title

    Recognizing mental stress in chess players using vital sign data

  • Author

    Eggert, Christian ; Lara, Oscar D. ; Labrador, M.A.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA
  • fYear
    2013
  • fDate
    4-7 April 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The identification of psychological stress can provide important feedback in order to perform critical activities. While a certain amount of stress may increase performance, an overly stressful reaction may hinder it. Because subjective bias can make it difficult to accurately recognize psychological stress, it would be advantageous for an external system to perform the task instead. We present a platform for psychological stress detection using physiological sensors during a chess match. The sensors are inside an unobtrusive chest strap that can be worn by the player during a match. By playing games on an Android phone, the system can apply machine learning techniques to the player´s vital sign data to give important feedback such as which moves caused the player to become stressed during a match.
  • Keywords
    Linux; computer games; learning (artificial intelligence); psychology; smart phones; Android phone; chess players; machine learning techniques; mental stress recognition; psychological stress identification; vital sign data; Feature extraction; Games; Heart rate; Physiology; Psychology; Sensors; Stress; Human activity recognition; structural pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Southeastcon, 2013 Proceedings of IEEE
  • Conference_Location
    Jacksonville, FL
  • ISSN
    1091-0050
  • Print_ISBN
    978-1-4799-0052-7
  • Type

    conf

  • DOI
    10.1109/SECON.2013.6567512
  • Filename
    6567512