The brain responses to SSVEP can be divided into three frequency bands: low frequency band (below 12 Hz), medium frequency band (12–30 Hz), and high frequency band (above 30 Hz) (Herrmann 2001 Wang et al. The potential change of the cerebral cortex in reaction to the visual stimulus is called the visual evoked potential. In recent years, information such as phase, color, and motion have been used to improve classification accuracy (Wittevrongel and Hulle 2016 Falzon et al. Thus, the user’s potential operating intent can be deduced (Chen et al. By recognizing the peak frequency of the electroencephalogram (EEG) induced by the stimulus, it is possible to identify the user’s focused target.
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The traditional SSVEP-BCI system uses a series of light-flashing modules with different frequencies as a stimulus, and each stimulus corresponds to an operation command. 2017 Müller-Putz and Pfurtscheller 2007 Lin et al. Steady-state visual evoked potential (SSVEP)-BCI has the advantage of a high information transfer rate (ITR), which has become a focus for researchers in recent years (Maye et al. The experimental results showed that the proposed method could be considered for practical BCI systems.īrain–computer interface (BCI) technology provides a way to advance interactions with the outside world for people who are disabled. The average accuracy was 92.96% and the information transfer rate was 26.10 bits/min. Moreover, the modulation between motion and light-flashing was weak. The experimental results showed that the hybrid paradigm could induce stable motion frequency, light-flashing frequency and its harmonic components. The motion frequency and the light-flashing frequency of the hybrid paradigm consisted of two frequencies in five frequencies. This study used five frequencies to encode nine targets. The motion and light-flashing patterns had different frequencies. The hybrid paradigm pattern consisted of a circular light-flashing pattern and a motion pattern located in the inner ring of light-flashing pattern.
To circumvent this, we proposed a brain–computer interface (BCI) method based on light-flashing and motion hybrid coding. This results in a reduced number of encoded targets. The human best response frequency band for steady-state visual evoked potential stimulus is limited.
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