Interictal EEG Denoising using Independent Component Analysis and Empirical Mode Decomposition

被引：0

作者：

Salsabili, Sina ^{[1
]}

Sardoui, Sepideh Hajipour ^{[2
]}

Shamsollahi, Mohammad B. ^{[2
]}

机构：

[1] Sharif Univ Technol, Sch Engn & Sci, Int Campus Kish Isl, Tehran, Iran

[2] Sharif Univ Technol, Sch Elect Engn, Biomed Signal & Image Proc Lab BiSIPL, Tehran, Iran

来源：

2015 38TH INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS AND SIGNAL PROCESSING (TSP) | 2015年

关键词：

Single Channel ICA; Multi-channel ICA denoising; EMD; Interictal Epileptic Spikes; Muscle artifact; EEG background activity;

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：

Noise contamination is inevitable in biomedical recordings. In some cases biomedical recordings are highly contaminated with artifacts which make the effective recovering process hard to achieve. Many different methods have been proposed for artifact removal from biomedical signals but introducing an effective method which can present valuable data for medical analysis, is still an ongoing process. In this paper a new method for interictal EEG denoising is presented. Single channel ICA denoising method based on EMD decomposition is used to improve the multi-channel ICA denoising results. This method is tested on simulated epileptic recordings which are contaminated with real muscle artifact and EEG background activity.

引用

页数：6

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