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A MUSIC-based method for SSVEP signal processing

  • Kun Chen
  • Quan LiuEmail author
  • Qingsong Ai
  • Zude Zhou
  • Sheng Quan Xie
  • Wei Meng
Scientific Paper

Abstract

The research on brain computer interfaces (BCIs) has become a hotspot in recent years because it offers benefit to disabled people to communicate with the outside world. Steady state visual evoked potential (SSVEP)-based BCIs are more widely used because of higher signal to noise ratio and greater information transfer rate compared with other BCI techniques. In this paper, a multiple signal classification based method was proposed for multi-dimensional SSVEP feature extraction. 2-second data epochs from four electrodes achieved excellent accuracy rates including idle state detection. In some asynchronous mode experiments, the recognition accuracy reached up to 100 %. The experimental results showed that the proposed method attained good frequency resolution. In most situations, the recognition accuracy was higher than canonical correlation analysis, which is a typical method for multi-channel SSVEP signal processing. Also, a virtual keyboard was successfully controlled by different subjects in an unshielded environment, which proved the feasibility of the proposed method for multi-dimensional SSVEP signal processing in practical applications.

Keywords

Brain computer interface (BCI) Steady state visual evoked potential (SSVEP) Multiple signal classification (MUSIC) Feature extraction 

Notes

Acknowledgments

This work was supported by the National Science Foundation (Grant No. 51475342). The authors would like to thank all subjects for their participating in the experiments.

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Copyright information

© Australasian College of Physical Scientists and Engineers in Medicine 2016

Authors and Affiliations

  • Kun Chen
    • 1
    • 3
  • Quan Liu
    • 2
    • 3
    Email author
  • Qingsong Ai
    • 2
    • 3
  • Zude Zhou
    • 1
    • 3
  • Sheng Quan Xie
    • 4
  • Wei Meng
    • 2
    • 3
  1. 1.School of Mechanical and Electronic EngineeringWuhan University of TechnologyWuhanChina
  2. 2.School of Information EngineeringWuhan University of TechnologyWuhanChina
  3. 3.Key Laboratory of Fiber Optic Sensing Technology and Information Processing Ministry of EducationWuhanChina
  4. 4.Department of Mechanical EngineeringThe University of AucklandAucklandNew Zealand

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