Performance Comparison of Wavelet and Multiwavelet Denoising Methods for an Electrocardiogram Signal

The increase in the occurrence of cardiovascular diseases in the world has made electrocardiogram an important tool to diagnose the various arrhythmias of the heart. But the recorded electrocardiogram often contains artefacts like power line noise, baseline noise, and muscle artefacts. Hence denoisi...

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Main Authors: Balambigai Subramanian, Asokan Ramasamy, Kamalakannan Rangasamy
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2014/241540
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spelling doaj-c3fe8a8f98554dc3835c8bc38d2fc6b02020-11-24T21:28:20ZengHindawi LimitedJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/241540241540Performance Comparison of Wavelet and Multiwavelet Denoising Methods for an Electrocardiogram SignalBalambigai Subramanian0Asokan Ramasamy1Kamalakannan Rangasamy2Department of Electronics and Communication Engineering, Kongu Engineering College, Perundurai, Erode District, Tamil Nadu 638052, IndiaKongunadu College of Engineering and Technology, Thottiyam, Trichy District, Tamil Nadu 621215, IndiaDepartment of Electronics and Communication Engineering, Kongu Engineering College, Perundurai, Erode District, Tamil Nadu 638052, IndiaThe increase in the occurrence of cardiovascular diseases in the world has made electrocardiogram an important tool to diagnose the various arrhythmias of the heart. But the recorded electrocardiogram often contains artefacts like power line noise, baseline noise, and muscle artefacts. Hence denoising of electrocardiogram signals is very important for accurate diagnosis of heart diseases. The properties of wavelets and multiwavelets have better denoising capability compared to conventional filtering techniques. The electrocardiogram signals have been taken from the MIT-BIH arrhythmia database. The simulation results prove that there is a 29.7% increase in the performance of multiwavelets over the performance of wavelets in terms of signal to noise ratio (SNR).http://dx.doi.org/10.1155/2014/241540
collection DOAJ
language English
format Article
sources DOAJ
author Balambigai Subramanian
Asokan Ramasamy
Kamalakannan Rangasamy
spellingShingle Balambigai Subramanian
Asokan Ramasamy
Kamalakannan Rangasamy
Performance Comparison of Wavelet and Multiwavelet Denoising Methods for an Electrocardiogram Signal
Journal of Applied Mathematics
author_facet Balambigai Subramanian
Asokan Ramasamy
Kamalakannan Rangasamy
author_sort Balambigai Subramanian
title Performance Comparison of Wavelet and Multiwavelet Denoising Methods for an Electrocardiogram Signal
title_short Performance Comparison of Wavelet and Multiwavelet Denoising Methods for an Electrocardiogram Signal
title_full Performance Comparison of Wavelet and Multiwavelet Denoising Methods for an Electrocardiogram Signal
title_fullStr Performance Comparison of Wavelet and Multiwavelet Denoising Methods for an Electrocardiogram Signal
title_full_unstemmed Performance Comparison of Wavelet and Multiwavelet Denoising Methods for an Electrocardiogram Signal
title_sort performance comparison of wavelet and multiwavelet denoising methods for an electrocardiogram signal
publisher Hindawi Limited
series Journal of Applied Mathematics
issn 1110-757X
1687-0042
publishDate 2014-01-01
description The increase in the occurrence of cardiovascular diseases in the world has made electrocardiogram an important tool to diagnose the various arrhythmias of the heart. But the recorded electrocardiogram often contains artefacts like power line noise, baseline noise, and muscle artefacts. Hence denoising of electrocardiogram signals is very important for accurate diagnosis of heart diseases. The properties of wavelets and multiwavelets have better denoising capability compared to conventional filtering techniques. The electrocardiogram signals have been taken from the MIT-BIH arrhythmia database. The simulation results prove that there is a 29.7% increase in the performance of multiwavelets over the performance of wavelets in terms of signal to noise ratio (SNR).
url http://dx.doi.org/10.1155/2014/241540
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