A wavelet based algorithm for Ocular Artifact detection In the EEG signals

M. Kiamini, S. Alirezaee, B. Perseh, M. Ahmadi
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引用次数: 15

Abstract

Artifacts are noises introduced to an electroencephalogram (EEG) signal by patient's movements. Eye-blinks and movements of the eyeballs produce electrical signals that are collectively known as Ocular Artifacts (OA) and these are 10-100 times stronger than EEG signal which is being recorded. Removing artifacts from EEG signal may aid the work of doctors, because artifacts disturb their attention. This paper present a new method to automatically identify the position of Ocular Artifacts zones in contaminated EEG signal. Then only removing it's to obtain clean EEG based on the stationary wavelet transform (SWT). In this case, correlation coefficient between wavelet coefficients of the Ocular Artifacts zones in contaminated EEG signal and same zones in electrooculogram (EOG) will be used to generate the wavelet coefficients for artifact-free EEG signal.
基于小波的脑电信号眼伪影检测算法
伪影是由患者的运动引入到脑电图信号中的噪声。眨眼和眼球运动产生的电信号统称为眼伪影(OA),这些信号比记录的脑电图信号强10-100倍。去除脑电图信号中的伪影可能有助于医生的工作,因为伪影会干扰他们的注意力。提出了一种自动识别受污染脑电信号中眼伪影区位置的新方法。然后基于平稳小波变换(SWT)将其去除,得到干净的脑电信号。在这种情况下,将利用污染脑电信号中眼伪影区域的小波系数与眼电图中相同区域的小波系数之间的相关系数来生成无伪影脑电信号的小波系数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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