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Proceedings Paper

Empirical mode decomposition of the ECG signal for noise removal
Author(s): Jesmin Khan; Sharif Bhuiyan; Gregory Murphy; Mohammad Alam
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Paper Abstract

Electrocardiography is a diagnostic procedure for the detection and diagnosis of heart abnormalities. The electrocardiogram (ECG) signal contains important information that is utilized by physicians for the diagnosis and analysis of heart diseases. So good quality ECG signal plays a vital role for the interpretation and identification of pathological, anatomical and physiological aspects of the whole cardiac muscle. However, the ECG signals are corrupted by noise which severely limit the utility of the recorded ECG signal for medical evaluation. The most common noise presents in the ECG signal is the high frequency noise caused by the forces acting on the electrodes. In this paper, we propose a new ECG denoising method based on the empirical mode decomposition (EMD). The proposed method is able to enhance the ECG signal upon removing the noise with minimum signal distortion. Simulation is done on the MIT-BIH database to verify the efficacy of the proposed algorithm. Experiments show that the presented method offers very good results to remove noise from the ECG signal.

Paper Details

Date Published: 26 April 2011
PDF: 12 pages
Proc. SPIE 8055, Optical Pattern Recognition XXII, 805504 (26 April 2011); doi: 10.1117/12.884744
Show Author Affiliations
Jesmin Khan, Tuskegee Univ. (United States)
Sharif Bhuiyan, Tuskegee Univ. (United States)
Gregory Murphy, Tuskegee Univ. (United States)
Mohammad Alam, Univ. of South Alabama (United States)


Published in SPIE Proceedings Vol. 8055:
Optical Pattern Recognition XXII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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