Denoising ECG signal based on ensemble empirical mode decomposition

Zhao Zhi-dong; Juan Liu; Sheng-tao Wang

doi:10.1117/12.913515

1 October 2011 Denoising ECG signal based on ensemble empirical mode decomposition

Zhao Zhi-dong, Juan Liu, Sheng-tao Wang

Proceedings Volume 8285, International Conference on Graphic and Image Processing (ICGIP 2011); 828577 (2011) https://doi.org/10.1117/12.913515
Event: 2011 International Conference on Graphic and Image Processing, 2011, Cairo, Egypt

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.

Citation Download Citation

Zhao Zhi-dong, Juan Liu, and Sheng-tao Wang "Denoising ECG signal based on ensemble empirical mode decomposition", Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 828577 (1 October 2011); https://doi.org/10.1117/12.913515

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