Study on SSVEP response under the checkerboard stimulus pattern based on improved 2D-EEMD

In the Brain-Computer Interface (BCI) system, brain activities can be translated into command for a computer without depending on the normal brain signal output pathway. Steady-State Visual Evoked Potential (SSVEP), one of these rhythmic brain signals induced by Repetitive Visual Stimulus (RVS), is widely used in studies. Different RVS results in the performance difference of BCI system. This paper uses an improved two-dimensional Ensemble Empirical Mode Decomposition (2D-EEMD) algorithm to pretreat the response signal and study the response performance of SSVEP in the various regions of the brain under the checkerboard stimulus. The improved 2D-EEMD introduced according to the feature of EEG can get a clearer two-dimensional decomposition result and improve the accuracy of the extraction response frequency. It decomposes the SSVEP separately in two orthogonal directions, and then recombines the decomposition results according to the “comparable minimal-scale combination strategy” to obtain the final two-dimensional decomposition result. The strategy removes the interference components from the decomposition results to prevent the effective characteristics of the SSVEP from being covered. This is more conducive to the extraction of signal characteristics. In contrast to a single-stimulus, SSVEP response shows significantly regional features under the checkerboard stimulus. The main response frequency is different in each brain area. Only in Left Occipital Lobe (LO) area, the main response frequency is consistent with visual stimulation frequency.