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

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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… Click to show full 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.

Keywords: fuzzy feature; game; maze game; ssvep based; bci; feature threshold

Journal Title: International Journal of Fuzzy Systems
Year Published: 2017

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