Method of removing EOG artifacts from EEG based on ICA

被引：0

作者：

Chen, LW ^{[1
]}

Bi, GT ^{[1
]}

Sun, M ^{[1
]}

Liao, J ^{[1
]}

Li, XY ^{[1
]}

机构：

[1] Soustwest Univ Sci & Technol, Sch Comp Sci & Technol, Mianyang 621010, Sichuan, Peoples R China

来源：

ICEMI 2005: Conference Proceedings of the Seventh International Conference on Electronic Measurement & Instruments, Vol 5 | 2005年

关键词：

ICA; EOG; artifacts;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Independent Component Analysis (ICA) is an emerging technique that can be used to remove artifacts associated with blinks, eye-movements, muscle noise, cardiac signals and line noise from EEG data-sets. Our example demonstrates that ICA can effectively remove EOG contamination of multi-channel EEG data. In our paper a fast fixed-point algorithm that is capable of separating complex values, linearly mixed source signal is proposed and EOG Artifacts shows its computational efficiency in removing Electrocardio-gram Artifacts from electroencephalographic (EEG).

引用

页码：458 / 460

页数：3

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