• DocumentCode
    864473
  • Title

    Steady-state somatosensory evoked potentials: suitable brain signals for brain-computer interfaces?

  • Author

    Muller-Putz, Gernot R. ; Scherer, Rafal ; Neuper, Christa ; Pfurtscheller, Gert

  • Author_Institution
    Lab. of Brain-Comput. Interfaces, Graz Univ. of Technol., Austria
  • Volume
    14
  • Issue
    1
  • fYear
    2006
  • fDate
    3/1/2006 12:00:00 AM
  • Firstpage
    30
  • Lastpage
    37
  • Abstract
    One of the main issues in designing a brain-computer interface (BCI) is to find brain patterns, which could easily be detected. One of these pattern is the steady-state evoked potential (SSEP). SSEPs induced through the visual sense have already been used for brain-computer communication. In this work, a BCI system is introduced based on steady-state somatosensory evoked potentials (SSSEPs). Transducers have been used for the stimulation of both index fingers using tactile stimulation in the "resonance"-like frequency range of the somatosensory system. Four subjects participated in the experiments and were trained to modulate induced SSSEPs. Two of them learned to modify the patterns in order to set up a BCI with an accuracy of between 70% and 80%. Results presented in this work give evidence that it is possible to set up a BCI which is based on SSSEPs.
  • Keywords
    bioelectric potentials; biomedical transducers; electroencephalography; handicapped aids; haptic interfaces; somatosensory phenomena; brain patterns; brain signals; brain-computer interfaces; index finger stimulation; steady-state somatosensory evoked potentials; tactile stimulation; transducers; visual sense; Biomedical informatics; Computer graphics; Electroencephalography; Feature extraction; Fingers; Frequency; Helium; Laboratories; Steady-state; Transducers; Brain–computer interface (BCI); electroencephalogram (EEG); steady-state somatosensory evoked potential (SSSEP); Adult; Biofeedback (Psychology); Brain; Electric Stimulation; Electroencephalography; Evoked Potentials, Somatosensory; Female; Fingers; Humans; Learning; Male; Movement; Signal Processing, Computer-Assisted; User-Computer Interface;
  • fLanguage
    English
  • Journal_Title
    Neural Systems and Rehabilitation Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1534-4320
  • Type

    jour

  • DOI
    10.1109/TNSRE.2005.863842
  • Filename
    1605261