Steady-state visual evoked potential (SSVEP) in a new paradigm containing dynamic fixation points

Abstract

Steady-state visual evoked potential (SSVEP) has become a powerful tool for Brain Computer Interface (BCI) because of its high signal-to-noise ratio, high information transmission rate, and minimal user training. At present, the edge information of each region cannot be identified in spatial coding based on SSVEP-BCI technology, and the user experience is poor. To solve this problem, this paper designed a new paradigm to explore the relationship between the fixation point position of continuous sliding and the correlation coefficient ratio in the dual-frequency case. Firstly, the standard sinusoidal signal was employed to simulate the Electroencephalogram (EEG) signal, which verified the reliability of characterizing the amplitude variation of test signal by correlation coefficient. Then, the relationship between the amplitude response of SSVEP and the distance between the fixation point and the stimulus in the horizontal direction was tested by Canonical Correlation Analysis (CCA) and Filter bank CCA (FBCCA). Finally, the experimental data were offline analyzed under the condition of continuous sliding of the fixation point. It is feasible and reasonable to detect the amplitude change of frequency component in SSVEP by utilizing the spatial coding method in this paper to improve the extraction accuracy of spatial information.