文章基本信息

标题：A Wavelet based Statistical Method for De-Noising of Ocular Artifacts in EEG Signals
作者：P. Senthil Kumar ; R. Arumuganathan ; K. Sivakumar 等
期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2008
卷号：8
期号：9
页码：87-92
出版社：International Journal of Computer Science and Network Security
摘要：This paper presents a new empirical method for de-noising of ocular artifacts in the electroencephalogram (EEG) records. In many biomedical signal processing approach, source signals are noisy and some have kurtosis close to zero. These noise sources increase the difficulty in analyzing the EEG and obtaining the clinical information. To remove this artifacts a method based on Donoho��s de-noising method is used. Recently Stationary Wavelet Transform (SWT) has been used to de-noise the corrupted EEG signals. In this paper, statistical empirical method for removing ocular artifacts from EEG recordings through SWT is suggested.
关键词：EEG; de-noising; ocular artifacts; stationary wavelet transform