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Study on SSVEP Response Under the Checkerboard Stimulus Pattern Based on Improved 2D-EEMD

机译:基于改进的2D-EEMD的棋角刺激模式下SSVEP反应研究

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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.
机译:在脑 - 计算机接口(BCI)系统中,可以在不取决于正常的脑信号输出路径的情况下将大脑活动转换为计算机。通过重复视觉刺激(RVS)引起的这些节奏脑信号之一,稳态视觉诱发电位(SSVEP)被广泛用于研究。不同的RVS导致BCI系统的性能差异。本文采用改进的二维集合经验模式分解(2D-EEMD)算法预处理响应信号,并在棋盘刺激下的脑部各个区域中的SSVEP响应性能。根据EEG的特征引入的改进的2D-EEMD可以获得更清晰的二维分解结果并提高提取响应频率的准确性。它在两个正交方向上单独分解SSVEP,然后根据“可比较的最小规模组合策略”重新组合分解结果以获得最终的二维分解结果。该策略从分解结果中删除干扰分量,以防止SSVEP的有效特性被覆盖。这更有利于提取信号特性。与单刺激相比,SSVEP响应显示在棋盘刺激下的显着区域特征。每个脑区域的主要响应频率不同。只有在左侧枕叶(LO)区域,主要响应频率与视觉刺激频率一致。

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