• DocumentCode
    527735
  • Title

    The training strategy in brain-computer interface

  • Author

    Xia, Bin ; Yang, Wenlu ; Xiao Dianyun ; Wang Cong

  • Author_Institution
    Coll. of Electron. & Inf. Eng., Tongji Univ., Shanghai, China
  • Volume
    4
  • fYear
    2010
  • fDate
    10-12 Aug. 2010
  • Firstpage
    2190
  • Lastpage
    2193
  • Abstract
    In this paper, we discuss the different train strategies for brain-computer interface. In general, it will take a long time to train subjects for motor imagery based BCI. There are many biofeedback methods to train subject. To compare the efficiency of different training strategies, we train the subjects by using two type training models: virtual reality and progress bar. The progress bar based training strategy show good result in our experiments.
  • Keywords
    brain-computer interfaces; virtual reality; biofeedback methods; brain-computer interface; motor imagery; progress bar based training strategy; training strategy; virtual reality; Accuracy; Electroencephalography; Feature extraction; Signal processing; Support vector machines; Training; Virtual reality; motor imagery; progress bar; virtual-reality;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation (ICNC), 2010 Sixth International Conference on
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-5958-2
  • Type

    conf

  • DOI
    10.1109/ICNC.2010.5583993
  • Filename
    5583993
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=527735