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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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 |
work_keys_str_mv |
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