Study on Optimal Selection of Wavelet Vanishing Moments for ECG Denoising

Abstract The frequency characteristics of wavelets and the vanishing moments of wavelet filters are both important parameters of wavelets. Clarifying the relationship between the wavelet frequency characteristics and the vanishing moments of the wavelet filter can provide a theoretical basis for sel...

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Autores principales:	Ziran Peng, Guojun Wang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/752303ff05874b9ea6d58a99385534d8
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spelling	oai:doaj.org-article:752303ff05874b9ea6d58a99385534d82021-12-02T15:05:16ZStudy on Optimal Selection of Wavelet Vanishing Moments for ECG Denoising10.1038/s41598-017-04837-92045-2322https://doaj.org/article/752303ff05874b9ea6d58a99385534d82017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-04837-9https://doaj.org/toc/2045-2322Abstract The frequency characteristics of wavelets and the vanishing moments of wavelet filters are both important parameters of wavelets. Clarifying the relationship between the wavelet frequency characteristics and the vanishing moments of the wavelet filter can provide a theoretical basis for selecting the best wavelet. In this paper, the frequency characteristics of wavelets were analyzed by mathematical modeling, the mathematical relationship between wavelet frequency characteristics and vanishing moments was clarified, the optimal wavelet base function was selected hierarchically according to the amplitude frequency characteristics of ECG signal, and an accurate notch filter was realized according to the frequency characteristics of the noise. The experimental results showed that the optimal orthogonal wavelet analysis for the ECG signals with different frequency characteristics could make the high frequency energy distribution sparser, and the method proposed in this paper could effectively preserve the singularity of the signal and reduce the signal distortion.Ziran PengGuojun WangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ziran Peng Guojun Wang Study on Optimal Selection of Wavelet Vanishing Moments for ECG Denoising
description	Abstract The frequency characteristics of wavelets and the vanishing moments of wavelet filters are both important parameters of wavelets. Clarifying the relationship between the wavelet frequency characteristics and the vanishing moments of the wavelet filter can provide a theoretical basis for selecting the best wavelet. In this paper, the frequency characteristics of wavelets were analyzed by mathematical modeling, the mathematical relationship between wavelet frequency characteristics and vanishing moments was clarified, the optimal wavelet base function was selected hierarchically according to the amplitude frequency characteristics of ECG signal, and an accurate notch filter was realized according to the frequency characteristics of the noise. The experimental results showed that the optimal orthogonal wavelet analysis for the ECG signals with different frequency characteristics could make the high frequency energy distribution sparser, and the method proposed in this paper could effectively preserve the singularity of the signal and reduce the signal distortion.
format	article
author	Ziran Peng Guojun Wang
author_facet	Ziran Peng Guojun Wang
author_sort	Ziran Peng
title	Study on Optimal Selection of Wavelet Vanishing Moments for ECG Denoising
title_short	Study on Optimal Selection of Wavelet Vanishing Moments for ECG Denoising
title_full	Study on Optimal Selection of Wavelet Vanishing Moments for ECG Denoising
title_fullStr	Study on Optimal Selection of Wavelet Vanishing Moments for ECG Denoising
title_full_unstemmed	Study on Optimal Selection of Wavelet Vanishing Moments for ECG Denoising
title_sort	study on optimal selection of wavelet vanishing moments for ecg denoising
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/752303ff05874b9ea6d58a99385534d8
work_keys_str_mv	AT ziranpeng studyonoptimalselectionofwaveletvanishingmomentsforecgdenoising AT guojunwang studyonoptimalselectionofwaveletvanishingmomentsforecgdenoising
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Study on Optimal Selection of Wavelet Vanishing Moments for ECG Denoising

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