• DocumentCode
    1674317
  • Title

    Non-invasive brain signal interface for a wheelchair navigation

  • Author

    Shin, Bong-Gun ; Kim, Taesoo ; Jo, Sungho

  • Author_Institution
    Dept. of Comput. Sci., KAIST, Daejeon, South Korea
  • fYear
    2010
  • Firstpage
    2257
  • Lastpage
    2260
  • Abstract
    This work presents that, only using non-invasively captured brain signals, a person can navigate an electric wheelchair with no serious training for a long term. Only two electrodes are set on the scalp non-invasively to detect a P300 EEG signal and a reference signal. A simple signal processing interprets the measured signals to decide a movement direction of the wheelchair. The whole devices are loaded on the wheelchair. No external system is required. The experimental results demonstrate the feasibility of the simple BCI processing to achieve reasonable performance.
  • Keywords
    brain-computer interfaces; electroencephalography; medical signal processing; signal detection; wheelchairs; BCI processing; P300 EEG signal detection; electric wheelchair; noninvasive brain signal interface; reference signal detection; signal measurement; signal processing; wheelchair navigation; Computers; DC motors; Electrodes; Electroencephalography; Navigation; Training; Wheelchairs; Brain-machine interface; EEG; P300; wheelchair control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Automation and Systems (ICCAS), 2010 International Conference on
  • Conference_Location
    Gyeonggi-do
  • Print_ISBN
    978-1-4244-7453-0
  • Electronic_ISBN
    978-89-93215-02-1
  • Type

    conf

  • Filename
    5669830