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首页> 外文期刊>Procedia Computer Science >A New Method for Automatic Electrooculogram and Eye Blink Artifacts Correction of EEG Signals using CCA and NAPCT
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A New Method for Automatic Electrooculogram and Eye Blink Artifacts Correction of EEG Signals using CCA and NAPCT

机译：使用CCA和NAPCT自动电帘图和眼睛眨眼伪装伪像校正的新方法

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摘要

Eye movements during electroencephalogram (EEG) recordings are the major sources of artifacts. These artifacts tend to mask the EEG signals. So, to obtain good quality EEG signals, these artifacts must be removed without deteriorating the underlying EEG activity. In this paper, a new algorithm is proposed that combines canonical correlation analysis (CCA) and noise adjusted principal component transform (NAPCT) to efficiently remove the electrooculogram (EOG) and blink artifacts in a considerably fast manner. CCA-NAPCT is implemented after the preliminary outlier thresholding of EEG data. CCA is used to estimate the noise covariance matrix while NAPCT is implemented for noise removal. The results of this algorithm on EOG affected BCI competition III dataset IVb and blink contaminated EEG data of four subjects showed the efficacy of the proposed algorithm in effective removal of noise. The algorithm provides an average signal to noise ratio and root mean square error values of 3.616 & 42.456 with artifactual EEG data respectively. Moreover, the average correlation coefficients (0.8839) and mutual information (1.1546) values also verify the efficacy of algorithm more firmly as supported by comparison with the state-of-the-art technique. The proposed algorithm successfully removed the artifactual components with no manual intervention.
机译：脑电图期间的眼睛运动（EEG）记录是伪影的主要来源。这些伪影倾向于掩盖EEG信号。因此，为了获得良好的EEG信号，必须在不恶化潜在的脑电图活动的情况下移除这些伪影。在本文中，提出了一种新的算法，其结合了规范相关性分析（CCA）和噪声调整的主成分变换（NAPCT）以有效地去除电帘图（EOG）并以相当快的方式闪烁伪像。 CCA-NAPCT在EEG数据的初步异常阈值下实现。 CCA用于估计噪声协方差矩阵，而NAPCT被实现用于噪声去除。该算法在EOG中受影响的BCI竞赛III数据集IVB和四个受试者的眨眼污染的EEG数据显示了所提出的算法在有效地去除噪声中的功效。该算法分别提供了与艺术eEG数据的3.616＆42.456的平均信号和均均方误差值。此外，平均相关系数（0.8839）和互信息（1.1546）的值还更牢固地验证算法的功效，通过与最先进的技术进行比较。所提出的算法成功地删除了没有手动干预的艺术组件。

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