首页> 外文会议>2017 Signal Processing: Algorithms, Architectures, Arrangements, and Applications >Correction of eye-blink artifacts in EEG recordings using Wiener filtering
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Correction of eye-blink artifacts in EEG recordings using Wiener filtering

机译:使用维纳滤波校正EEG记录中的眨眼伪像

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摘要

A novel method for removing eye-blink artifacts from brain EEG recordings is presented. It is proposed to use multichannel Wiener filter (MWF) indirectly. Namely, the eye-blink signal estimate is obtained first. For this purpose only a small subset of the frontal electrodes is used (so that extra EOG sensors are unnecessary). Then, the eye-blink estimate is subtracted from the noisy EEG signal in accordance with the regression technique. We have performed numerical experiments and compared this method to the commonly used independent component analysis (ICA) approach. Our experiments show that the proposed method can perform similarly to or even better than the ICA-based method. However, the MWF-based approach is much simpler and less computationally demanding.
机译:提出了一种从脑电图记录中去除眨眼伪像的新方法。建议间接使用多通道维纳滤波器(MWF)。即,首先获得眨眼信号估计。为此,仅使用一小部分正面电极(因此不需要额外的EOG传感器)。然后,根据回归技术从嘈杂的EEG信号中减去眨眼估计。我们已经进行了数值实验,并将此方法与常用的独立成分分析(ICA)方法进行了比较。我们的实验表明,所提出的方法可以与基于ICA的方法相似甚至更好。但是,基于MWF的方法更加简单,对计算的要求也更低。

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