A wavelet method for the noise reduction in electrocardiographic signals

Ye Wu; Yunfeng Wu; Sin Chun Ng; Yachao Zhou; Ruifan Li; Yixin Zhong

doi:10.1109/ICWAPR.2007.4421757

A wavelet method for the noise reduction in electrocardiographic signals

Ye Wu
, Yunfeng Wu
, Sin Chun Ng
, Yachao Zhou
, Ruifan Li
, Yixin Zhong

Hong Kong Metropolitan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The electrocardiogram (ECG) is the routinely used biomedical signal for diagnosis of cardiovascular diseases, and the removal of noise in ambulatory ECG recordings is essential in a number of clinical applications. In this paper, we present a Daubechies wavelet analysis method with a decomposition tree of level 5 (Wdb5) for analysis of noisy ECG signals. The implementation includes the procedures of signal decomposition and reconstruction with hard-thresholding. The experiments were tested with seven ambulatory ECG records from the benchmark MIT-BIH Arrythmia Database, and our results demonstrate the effectiveness of the Wdb5 analysis method for the noise reduction in ECG signals. Furthermore, the quantitative study of result evaluation indicates that the Wdb5 filtering method is superior to the popular least-mean-square (LMS) filter by achieving significantly higher signal-to-noise ratio and better filtered-noise entropy values.

Original language	English
Title of host publication	Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07
Pages	1857-1861
Number of pages	5
DOIs	https://doi.org/10.1109/ICWAPR.2007.4421757
Publication status	Published - 2007
Event	2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07 - Beijing, China Duration: 2 Nov 2007 → 4 Nov 2007

Publication series

Name	Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07
Volume	4

Conference

Conference	2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07
Country/Territory	China
City	Beijing
Period	2/11/07 → 4/11/07

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Electrocardiogram
Noise reduction
Wavelet analysis

Access to Document

10.1109/ICWAPR.2007.4421757

Cite this

Wu, Y., Wu, Y., Ng, S. C., Zhou, Y., Li, R., & Zhong, Y. (2007). A wavelet method for the noise reduction in electrocardiographic signals. In Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07 (pp. 1857-1861). Article 4421757 (Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07; Vol. 4). https://doi.org/10.1109/ICWAPR.2007.4421757

@inproceedings{f1a75d26ee3a4a1aa5bcb983ffda2c3a,

title = "A wavelet method for the noise reduction in electrocardiographic signals",

abstract = "The electrocardiogram (ECG) is the routinely used biomedical signal for diagnosis of cardiovascular diseases, and the removal of noise in ambulatory ECG recordings is essential in a number of clinical applications. In this paper, we present a Daubechies wavelet analysis method with a decomposition tree of level 5 (Wdb5) for analysis of noisy ECG signals. The implementation includes the procedures of signal decomposition and reconstruction with hard-thresholding. The experiments were tested with seven ambulatory ECG records from the benchmark MIT-BIH Arrythmia Database, and our results demonstrate the effectiveness of the Wdb5 analysis method for the noise reduction in ECG signals. Furthermore, the quantitative study of result evaluation indicates that the Wdb5 filtering method is superior to the popular least-mean-square (LMS) filter by achieving significantly higher signal-to-noise ratio and better filtered-noise entropy values.",

keywords = "Electrocardiogram, Noise reduction, Wavelet analysis",

author = "Ye Wu and Yunfeng Wu and Ng, \{Sin Chun\} and Yachao Zhou and Ruifan Li and Yixin Zhong",

year = "2007",

doi = "10.1109/ICWAPR.2007.4421757",

language = "English",

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series = "Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07",

pages = "1857--1861",

booktitle = "Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07",

note = "2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07 ; Conference date: 02-11-2007 Through 04-11-2007",

}

Wu, Y, Wu, Y, Ng, SC, Zhou, Y, Li, R & Zhong, Y 2007, A wavelet method for the noise reduction in electrocardiographic signals. in Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07., 4421757, Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07, vol. 4, pp. 1857-1861, 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07, Beijing, China, 2/11/07. https://doi.org/10.1109/ICWAPR.2007.4421757

A wavelet method for the noise reduction in electrocardiographic signals. / Wu, Ye; Wu, Yunfeng; Ng, Sin Chun et al.
Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07. 2007. p. 1857-1861 4421757 (Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07; Vol. 4).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A wavelet method for the noise reduction in electrocardiographic signals

AU - Wu, Ye

AU - Wu, Yunfeng

AU - Ng, Sin Chun

AU - Zhou, Yachao

AU - Li, Ruifan

AU - Zhong, Yixin

PY - 2007

Y1 - 2007

N2 - The electrocardiogram (ECG) is the routinely used biomedical signal for diagnosis of cardiovascular diseases, and the removal of noise in ambulatory ECG recordings is essential in a number of clinical applications. In this paper, we present a Daubechies wavelet analysis method with a decomposition tree of level 5 (Wdb5) for analysis of noisy ECG signals. The implementation includes the procedures of signal decomposition and reconstruction with hard-thresholding. The experiments were tested with seven ambulatory ECG records from the benchmark MIT-BIH Arrythmia Database, and our results demonstrate the effectiveness of the Wdb5 analysis method for the noise reduction in ECG signals. Furthermore, the quantitative study of result evaluation indicates that the Wdb5 filtering method is superior to the popular least-mean-square (LMS) filter by achieving significantly higher signal-to-noise ratio and better filtered-noise entropy values.

AB - The electrocardiogram (ECG) is the routinely used biomedical signal for diagnosis of cardiovascular diseases, and the removal of noise in ambulatory ECG recordings is essential in a number of clinical applications. In this paper, we present a Daubechies wavelet analysis method with a decomposition tree of level 5 (Wdb5) for analysis of noisy ECG signals. The implementation includes the procedures of signal decomposition and reconstruction with hard-thresholding. The experiments were tested with seven ambulatory ECG records from the benchmark MIT-BIH Arrythmia Database, and our results demonstrate the effectiveness of the Wdb5 analysis method for the noise reduction in ECG signals. Furthermore, the quantitative study of result evaluation indicates that the Wdb5 filtering method is superior to the popular least-mean-square (LMS) filter by achieving significantly higher signal-to-noise ratio and better filtered-noise entropy values.

KW - Electrocardiogram

KW - Noise reduction

KW - Wavelet analysis

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DO - 10.1109/ICWAPR.2007.4421757

M3 - Conference contribution

AN - SCOPUS:45149125538

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SN - 9781424410668

T3 - Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07

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BT - Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07

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ER -

Wu Y, Wu Y, Ng SC, Zhou Y, Li R, Zhong Y. A wavelet method for the noise reduction in electrocardiographic signals. In Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07. 2007. p. 1857-1861. 4421757. (Proceedings of the 2007 International Conference on Wavelet Analysis and Pattern Recognition, ICWAPR '07). doi: 10.1109/ICWAPR.2007.4421757

A wavelet method for the noise reduction in electrocardiographic signals

Abstract

Publication series

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UN SDGs

Keywords

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