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A Single-Channel SSVEP-Based BCI with a Fuzzy Feature Threshold Algorithm in a Maze Game

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Abstract

A mobile robot control in a maze game using steady-state visually evoked potential (SSVEP)-based brain–computer interface (BCI) is developed to help the severely disabled. In order to correctively induce the SSVEP of subjects, four visual stimuli including “counterclockwise,” “clockwise,” “forward,” and “backward” are displayed on monitor and flickering at different frequencies. The spectral features of EEG are extracted by using fast Fourier transform to accurately represent the characteristics of SSVEP. A fuzzy feature threshold algorithm is proposed to track the power spectrum of EEG and automatically adjust the threshold of EEG spectrum to achieve a suitable performance and stability of a BCI system. In this study, the system accuracies were 86.58 and 85.54% for robot movement simulation test and real robot control, respectively. Then, it would be suitable for the severely disabled to control the mobile robot in a maze game.

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Acknowledgements

The authors would like to appreciate the Ministry of Science and Technology of the Republic of China, Taiwan, for financially supporting this research under Contract MOST 105-2221-E-218-027, MOST 105-2221-E-218-015, and MOST 105-2221-E-168-021.

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Authors and Affiliations

  1. Department of Electrical Engineering, Southern Taiwan University of Science and Technology, Tainan, Taiwan

    Shih-Chung Chen, Yeou-Jiunn Chen & Ilham A. E. Zaeni

  2. Department of Computer and Communication, Kun-Shan University, Tainan, Taiwan

    Chung-Min Wu

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  1. Shih-Chung Chen
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  2. Yeou-Jiunn Chen
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  3. Ilham A. E. Zaeni
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Correspondence to Chung-Min Wu.

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Chen, SC., Chen, YJ., Zaeni, I.A.E. et al. A Single-Channel SSVEP-Based BCI with a Fuzzy Feature Threshold Algorithm in a Maze Game. Int. J. Fuzzy Syst. 19, 553–565 (2017). https://doi.org/10.1007/s40815-016-0289-3

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