• DocumentCode
    2865572
  • Title

    Detecting the attention state of an operator in continuous attention task using EEG-based brain-computer interface

  • Author

    Mishchenko, Yuriy ; Kaya, Murat

  • Author_Institution
    Bilgisayar-Yazilim Muhendisligi Bolumu, Toros Univ., Mersin, Turkey
  • fYear
    2015
  • fDate
    16-19 May 2015
  • Firstpage
    232
  • Lastpage
    235
  • Abstract
    Modern rapid developments of robotic and automated systems created novel operating environments for machinery and industrial process operators in which the reduction of the level of control exercised by operators can lead to their losing attention during important machinery or process operation tasks. Loss of attention is currently one of the most important causes of work and traffic related accidents. The problem of detecting the loss of operator´s attention attracted substantial attention in recent years. In this work, an EEG and SVM-based Brain-Computer Interface system was developed for determining an operator´s attention state. Using a virtual continuous attention vehicle control task, the ability of the system to detect different operator attention states with high degree of reliability was demonstrated.
  • Keywords
    brain-computer interfaces; electroencephalography; medical signal detection; support vector machines; EEG-based brain-computer interface; SVM-based brain-computer interface system; automated systems; continuous attention task; electroencephalography; operator attention state detection; reliability degree; robotic systems; support vector machines; Brain-computer interfaces; Electroencephalography; MATLAB; Real-time systems; Robots; Support vector machines; Vehicles; EEG BCI; SVM; attention loss; attention state determination;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2015 23th
  • Conference_Location
    Malatya
  • Type

    conf

  • DOI
    10.1109/SIU.2015.7129802
  • Filename
    7129802