• DocumentCode
    3661940
  • Title

    Brain-controlled wheelchair based EEG-SSVEP signals classified by nonlinear adaptive filter

  • Author

    Arjon Turnip;M. Agung Suhendra; Mada Sanjaya W. S.

  • Author_Institution
    Technical Implementation Unit for Instrumentation Development, Indonesian Institute of Sciences, Bandung, Indonesia
  • fYear
    2015
  • Firstpage
    905
  • Lastpage
    908
  • Abstract
    In this paper, an extraction for brain-controlled wheelchair by applying nonlinear adaptive filter on EEG-SSVEP is proposed. A four-choice signal paradigm with differents frequencies (i.e., from 6 to 9 Hz for left, right, bottom, and top, respectively) is used to stimulate the four subjects (about 25±1 years old) in the experiment. The experimental results show that the application of the extraction method achieves a very significant statistical improvement in extracting peak amplitude features.
  • Keywords
    "Feature extraction","Wheelchairs","Biological neural networks","Electroencephalography","Adaptive filters","Visualization","Noise"
  • Publisher
    ieee
  • Conference_Titel
    Rehabilitation Robotics (ICORR), 2015 IEEE International Conference on
  • ISSN
    1945-7898
  • Electronic_ISBN
    1945-7901
  • Type

    conf

  • DOI
    10.1109/ICORR.2015.7281318
  • Filename
    7281318