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Proceedings Paper

Denoising ECG signal based on ensemble empirical mode decomposition
Author(s): Zhao Zhi-dong; Juan Liu; Sheng-tao Wang
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Paper Abstract

The electrocardiogram (ECG) has been used extensively for detection of heart disease. Frequently the signal is corrupted by various kinds of noise such as muscle noise, electromyogram (EMG) interference, instrument noise etc. In this paper, a new ECG denoising method is proposed based on the recently developed ensemble empirical mode decomposition (EEMD). Noisy ECG signal is decomposed into a series of intrinsic mode functions (IMFs). The statistically significant information content is build by the empirical energy model of IMFs. Noisy ECG signal collected from clinic recording is processed using the method. The results show that on contrast with traditional methods, the novel denoising method can achieve the optimal denoising of the ECG signal.

Paper Details

Date Published: 1 October 2011
PDF: 7 pages
Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 828577 (1 October 2011); doi: 10.1117/12.913515
Show Author Affiliations
Zhao Zhi-dong, Hangzhou Dianzi Univ. (China)
Juan Liu, Hangzhou Dianzi Univ. (China)
Sheng-tao Wang, Hangzhou Dianzi Univ. (China)

Published in SPIE Proceedings Vol. 8285:
International Conference on Graphic and Image Processing (ICGIP 2011)
Yi Xie; Yanjun Zheng, Editor(s)

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