• DocumentCode
    3575638
  • Title

    Adaptive strategy for time window length in SSVEP-based brain-computer interface

  • Author

    Yu Zhang ; Hehe Ma ; Jing Jin ; Xingyu Wang

  • Author_Institution
    Key Lab. for Adv. Control & Optimization for Chem. Processes, East China Univ. of Sci. & Technol., Shanghai, China
  • fYear
    2014
  • Firstpage
    140
  • Lastpage
    143
  • Abstract
    Most of the existed methods for steady-state visual evoked potential (SSVEP) recognition require a specified time window length (TWL) to estimate the dominant frequency components in EEG signals. Typically, the TWL is manually predetermined and then fixed during running of the SSVEP-based brain-computer interface (BCI), which may not give the optimal information transfer rate (ITR). This study proposes an adaptive strategy and integrates it into multivariate synchronization index for SSVEP recognition with the automatically determined TWL. The optimal TWL is adaptively selected according to the estimated synchronization index, which provides the relatively higher ITR for the SSVEP recognition than a fixed TWL does. Experimental results evaluated on nine healthy subjects demonstrated effectiveness of the proposed adaptive strategy for the TWL in SSVEP-based BCI.
  • Keywords
    brain-computer interfaces; electroencephalography; medical signal detection; synchronisation; visual evoked potentials; BCI; EEG signals; ITR; SSVEP recognition; SSVEP-based brain-computer interface; adaptive strategy; information transfer rate; multivariate synchronization index; steady-state visual evoked potential; time window length; Accuracy; Brain-computer interfaces; Correlation; Electroencephalography; Frequency synchronization; Indexes; Synchronization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Control (ICMC), 2014 International Conference on
  • Print_ISBN
    978-1-4799-2537-7
  • Type

    conf

  • DOI
    10.1109/ICMC.2014.7231535
  • Filename
    7231535