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-  2015 

基于二维集合经验模式分解的稳态视觉诱发电位目标检测研究

DOI: doi:10.7507/1001-5515.20150093

Keywords: 脑机接口, 视觉稳态诱发电位, 二维集合经验模式分解, 本征模式函数, 短时傅里叶变换, 准确率

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Abstract:

稳态视觉诱发电位(SSVEP)是由持续的视觉刺激而诱发的节律性脑电信号。SSVEP频率由固定的视觉刺激频率及其谐波频率组成。二维集合经验模式分解(2D-EEMD)是经典的经验模式分解算法的改进算法, 将分解拓展到二维方向上。本文首创性地将2D-EEMD应用于SSVEP。分解得到的本征模式函数(IMF)的二维图像可清晰地观测到SSVEP频率。经过噪声和伪迹滤除的SSVEP主要有效IMF成分投影到头图上, 可以反映大脑对视觉刺激的时变趋势, 以及大脑不同区域的反应程度, 结果显示枕叶区对于视觉刺激的反应最为强烈。最后本文用短时傅里叶变换(STFT)对2D-EEMD的重构信号进行SSVEP频率提取, 其识别准确率提高了16%

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