ECG signals denoising using wavelet transform and independent component analysis

Manjin Liu; Mei Hui; Ming Liu; Liquan Dong; Zhu Zhao; Yuejin Zhao

doi:10.1117/12.2193108

ECG signals denoising using wavelet transform and independent component analysis

Manjin Liu
, Mei Hui^*
, Ming Liu
, Liquan Dong
, Zhu Zhao
, Yuejin Zhao

^*Corresponding author for this work

School of Optics and Photonics

Beijing Institute of Technology

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

2 Citations (Scopus)

Abstract

A method of two channel exercise electrocardiograms (ECG) signals denoising based on wavelet transform and independent component analysis is proposed in this paper. First of all, two channel exercise ECG signals are acquired. We decompose these two channel ECG signals into eight layers and add up the useful wavelet coefficients separately, getting two channel ECG signals with no baseline drift and other interference components. However, it still contains electrode movement noise, power frequency interference and other interferences. Secondly, we use these two channel ECG signals processed and one channel signal constructed manually to make further process with independent component analysis, getting the separated ECG signal. We can see the residual noises are removed effectively. Finally, comparative experiment is made with two same channel exercise ECG signals processed directly with independent component analysis and the method this paper proposed, which shows the indexes of signal to noise ratio (SNR) increases 21.916 and the root mean square error (MSE) decreases 2.522, proving the method this paper proposed has high reliability.

Original language	English
Title of host publication	2015 International Conference on Optical Instruments and Technology
Subtitle of host publication	Optoelectronic Imaging and Processing Technology, OIT 2015
Editors	Guangming Shi, Bormin Huang, Xuelong Li
Publisher	SPIE
ISBN (Electronic)	9781628418033
DOIs	https://doi.org/10.1117/12.2193108
Publication status	Published - 2015
Event	2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, OIT 2015 - Beijing, China Duration: 17 May 2015 → 19 May 2015

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	9622
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, OIT 2015
Country/Territory	China
City	Beijing
Period	17/05/15 → 19/05/15

Keywords

exercise ECG signals
independent component analysis
two channel
wavelet transform

Access to Document

10.1117/12.2193108

Cite this

Liu, M., Hui, M., Liu, M., Dong, L., Zhao, Z., & Zhao, Y. (2015). ECG signals denoising using wavelet transform and independent component analysis. In G. Shi, B. Huang, & X. Li (Eds.), 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, OIT 2015 Article 962213 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 9622). SPIE. https://doi.org/10.1117/12.2193108

Liu, Manjin ; Hui, Mei ; Liu, Ming et al. / ECG signals denoising using wavelet transform and independent component analysis. 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, OIT 2015. editor / Guangming Shi ; Bormin Huang ; Xuelong Li. SPIE, 2015. (Proceedings of SPIE - The International Society for Optical Engineering).

@inproceedings{7e1925d8cf7f428686932ffa35b98702,

title = "ECG signals denoising using wavelet transform and independent component analysis",

abstract = "A method of two channel exercise electrocardiograms (ECG) signals denoising based on wavelet transform and independent component analysis is proposed in this paper. First of all, two channel exercise ECG signals are acquired. We decompose these two channel ECG signals into eight layers and add up the useful wavelet coefficients separately, getting two channel ECG signals with no baseline drift and other interference components. However, it still contains electrode movement noise, power frequency interference and other interferences. Secondly, we use these two channel ECG signals processed and one channel signal constructed manually to make further process with independent component analysis, getting the separated ECG signal. We can see the residual noises are removed effectively. Finally, comparative experiment is made with two same channel exercise ECG signals processed directly with independent component analysis and the method this paper proposed, which shows the indexes of signal to noise ratio (SNR) increases 21.916 and the root mean square error (MSE) decreases 2.522, proving the method this paper proposed has high reliability.",

keywords = "exercise ECG signals, independent component analysis, two channel, wavelet transform",

author = "Manjin Liu and Mei Hui and Ming Liu and Liquan Dong and Zhu Zhao and Yuejin Zhao",

note = "Publisher Copyright: {\textcopyright} 2015 SPIE.; 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, OIT 2015 ; Conference date: 17-05-2015 Through 19-05-2015",

year = "2015",

doi = "10.1117/12.2193108",

language = "English",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

publisher = "SPIE",

editor = "Guangming Shi and Bormin Huang and Xuelong Li",

booktitle = "2015 International Conference on Optical Instruments and Technology",

address = "United States",

}

Liu, M, Hui, M, Liu, M , Dong, L, Zhao, Z & Zhao, Y 2015, ECG signals denoising using wavelet transform and independent component analysis. in G Shi, B Huang & X Li (eds), 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, OIT 2015., 962213, Proceedings of SPIE - The International Society for Optical Engineering, vol. 9622, SPIE, 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, OIT 2015, Beijing, China, 17/05/15. https://doi.org/10.1117/12.2193108

ECG signals denoising using wavelet transform and independent component analysis. / Liu, Manjin; Hui, Mei; Liu, Ming et al.
2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, OIT 2015. ed. / Guangming Shi; Bormin Huang; Xuelong Li. SPIE, 2015. 962213 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 9622).

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

TY - GEN

T1 - ECG signals denoising using wavelet transform and independent component analysis

AU - Liu, Manjin

AU - Hui, Mei

AU - Liu, Ming

AU - Dong, Liquan

AU - Zhao, Zhu

AU - Zhao, Yuejin

PY - 2015

Y1 - 2015

N2 - A method of two channel exercise electrocardiograms (ECG) signals denoising based on wavelet transform and independent component analysis is proposed in this paper. First of all, two channel exercise ECG signals are acquired. We decompose these two channel ECG signals into eight layers and add up the useful wavelet coefficients separately, getting two channel ECG signals with no baseline drift and other interference components. However, it still contains electrode movement noise, power frequency interference and other interferences. Secondly, we use these two channel ECG signals processed and one channel signal constructed manually to make further process with independent component analysis, getting the separated ECG signal. We can see the residual noises are removed effectively. Finally, comparative experiment is made with two same channel exercise ECG signals processed directly with independent component analysis and the method this paper proposed, which shows the indexes of signal to noise ratio (SNR) increases 21.916 and the root mean square error (MSE) decreases 2.522, proving the method this paper proposed has high reliability.

AB - A method of two channel exercise electrocardiograms (ECG) signals denoising based on wavelet transform and independent component analysis is proposed in this paper. First of all, two channel exercise ECG signals are acquired. We decompose these two channel ECG signals into eight layers and add up the useful wavelet coefficients separately, getting two channel ECG signals with no baseline drift and other interference components. However, it still contains electrode movement noise, power frequency interference and other interferences. Secondly, we use these two channel ECG signals processed and one channel signal constructed manually to make further process with independent component analysis, getting the separated ECG signal. We can see the residual noises are removed effectively. Finally, comparative experiment is made with two same channel exercise ECG signals processed directly with independent component analysis and the method this paper proposed, which shows the indexes of signal to noise ratio (SNR) increases 21.916 and the root mean square error (MSE) decreases 2.522, proving the method this paper proposed has high reliability.

KW - exercise ECG signals

KW - independent component analysis

KW - two channel

KW - wavelet transform

UR - https://www.scopus.com/pages/publications/84943577863

U2 - 10.1117/12.2193108

DO - 10.1117/12.2193108

M3 - Conference contribution

AN - SCOPUS:84943577863

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - 2015 International Conference on Optical Instruments and Technology

A2 - Shi, Guangming

A2 - Huang, Bormin

A2 - Li, Xuelong

PB - SPIE

T2 - 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, OIT 2015

Y2 - 17 May 2015 through 19 May 2015

ER -

Liu M, Hui M, Liu M , Dong L, Zhao Z, Zhao Y. ECG signals denoising using wavelet transform and independent component analysis. In Shi G, Huang B, Li X, editors, 2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, OIT 2015. SPIE. 2015. 962213. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.2193108

ECG signals denoising using wavelet transform and independent component analysis

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this