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The removal of blink and saccade artifact in EEG recordings by Independent Component Analysis

机译:通过独立分量分析去除脑电图记录中的眨眼和扫视伪像

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Pervasive electroencephalographic (EEG) artifacts are associated with eye movement. This study shows that Independent Component Analysis (ICA) using Joint Approximate Diagonalization of Eigenmatrice (JADE) algorithm can be applied to removing ocular artifacts in EEG. The nine channels of EEGs were recorded from three young healthy subjects with additional VEOG and HEOG channels in blinking and saccade conditions respectively. Seven EEG recordings were selected for artifacts removal tests with two EOG recordings indicating the possible interferences. Ocular artifacts for both conditions were successfully presented by an independent component, which was then eliminated to reconstruct the artifact-free EEGs. This study demonstrates that JADE algorithm can be an effective tool in correcting EOG interference with multichannel EEG recordings.
机译:普遍的脑电图(EEG)伪影与眼睛运动相关联。本研究表明,可以应用使用特征曲线(玉器)算法的关节近似对角线的独立分量分析(ICA)来消除EEG中的眼部伪影。脑电图的九个频道从三个年轻的健康受试者记录,其中额外的凸孔和Heog频道分别闪烁和扫视条件。选择七台脑电图录音为伪影删除测试,其中有两个EOG记录表明可能的干扰。两种条件的眼伪像由独立的组分成功呈现,然后被消除以重建无伪像脑电图。本研究表明,玉石算法可以是纠正与多通道EEG录像的EOG干扰的有效工具。

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