A novel hybrid BCI system based on SSVEP and EOG

The concept of hybrid brain-computer interface has been proposed in recent years. Hybrid BCI(HBCI) refers to a system that is a mixture of one single-mode BCI and another system (BCI system or non-BCI system). In this paper, we propose a new hybrid brain-computer interface which combines SSVEP and EOG to improve the performance of BCI system. The 16 buttons are distributed in four areas (upper left, lower left, upper right, and lower right) of the GUI, and the 16 buttons simultaneously start to flash, with the user staring at the target of his/her choice. After the flashing, the four positions will move in different directions, and the user generates the corresponding eye movement by watching the target. Since the time-domain features of EOG are very obvious during eye movement, the waveform analysis method used in this paper identifies the direction of eye movement. The TRCA algorithm is used to identify the SSVEP. At the same time, by fusing the features of EOG and SSVEP, the accuracy of the hybrid BCI system can be further improved. Ten healthy students participated in our experiment. The average classification accuracy of the system was 90.77%, and the information transmission rate (ITR) was 73.73 bits/min. Significance: These results show that the hybrid BCI system proposed in this paper has excellent performance.