• DocumentCode
    3684010
  • Title

    A brain computer interface for robust wheelchair control application based on pseudorandom code modulated Visual Evoked Potential

  • Author

    Ali Mohebbi;Signe K.D. Engelsholm;Sadasivan Puthusserypady;Troels W. Kjaer;Carsten E. Thomsen;Helge B.D. Sorensen

  • Author_Institution
    Technical University of Denmark, Department of Electrical Engineering, Ø
  • fYear
    2015
  • Firstpage
    602
  • Lastpage
    605
  • Abstract
    In this pilot study, a novel and minimalistic Brain Computer Interface (BCI) based wheelchair control application was developed. The system was based on pseudorandom code modulated Visual Evoked Potentials (c-VEPs). The visual stimuli in the scheme were generated based on the Gold code, and the VEPs were recognized and classified using subject-specific algorithms. The system provided the ability of controlling a wheelchair model (LEGO® MINDSTORM® EV3 robot) in 4 different directions based on the elicited c-VEPs. Ten healthy subjects were evaluated in testing the system where an average accuracy of 97% was achieved. The promising results illustrate the potential of this approach when considering a real wheelchair application.
  • Keywords
    "Robots","Wheelchairs","Electroencephalography","Visualization","Accuracy","Correlation","Brain-computer interfaces"
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE
  • ISSN
    1094-687X
  • Electronic_ISBN
    1558-4615
  • Type

    conf

  • DOI
    10.1109/EMBC.2015.7318434
  • Filename
    7318434