Based on Double-layer Stimulation SSVEP Character Input System

Brain-computer interface (BCI) is a communication system (computer or other device) independent of normal brain output pathway (peripheral nervous system and muscle tissue). An important use of the BCI is to provide language communication and environmental control pathways for those who have normal thinking but have severe dyskinesia. As a new type of communication channel, people with severe dyskinesia can communicate with the environment and participate in daily life. For BCI systems with multiple character input, when characters are added, the distance between characters decreases. In order to reduce the crowding effect caused by single-layer character input system, a double-layer steady-state visual evoked potential (SSVEP) character input system is designed. Experiments show that the accuracy of double-layer SSVEP is higher than that of single-layer SSVEP. It reduces the crowding effect by increasing the distance between characters. In this experiment, FBCCA (Filter Bank CCA) algorithm is used to extract eigenvalues. The results show that the accuracy of the double-layer visual steady-state system is 95.8%, and the average ITR (Information transfer rate) is 156 bit/min. The accuracy of the single-layer visual steady-state system is 92.1%,and average ITR is 146bit/min.