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Baseline Drift Removal and De-Noising of the ECG Signal using Wavelet Transform

by Iffat Ara, Md. Najmul Hossain, S. M. Yahea Mahbub
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 95 - Number 16
Year of Publication: 2014
Authors: Iffat Ara, Md. Najmul Hossain, S. M. Yahea Mahbub
10.5120/16678-6783

Iffat Ara, Md. Najmul Hossain, S. M. Yahea Mahbub . Baseline Drift Removal and De-Noising of the ECG Signal using Wavelet Transform. International Journal of Computer Applications. 95, 16 ( June 2014), 15-17. DOI=10.5120/16678-6783

@article{ 10.5120/16678-6783,
author = { Iffat Ara, Md. Najmul Hossain, S. M. Yahea Mahbub },
title = { Baseline Drift Removal and De-Noising of the ECG Signal using Wavelet Transform },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 95 },
number = { 16 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 15-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume95/number16/16678-6783/ },
doi = { 10.5120/16678-6783 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:19:36.687381+05:30
%A Iffat Ara
%A Md. Najmul Hossain
%A S. M. Yahea Mahbub
%T Baseline Drift Removal and De-Noising of the ECG Signal using Wavelet Transform
%J International Journal of Computer Applications
%@ 0975-8887
%V 95
%N 16
%P 15-17
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

ECG signal plays an important role in the primary diagnosis and analysis of heart diseases. When an Electrocardiogram is recorded many kinds of noise are recorded. The aim of this paper is to use discrete wavelet transform (DWT) for de-noising the ECG signal. Text formatted ECG signals of ten second duration are taken from the MIT-BIH arrhythmia database. ECG signal of Modified lead II (MLII) are chosen for processing. For wavelet transform, daubechies wavelets were used because the scaling functions of this wavelet filter are similar to the shape of the ECG. From the decomposition of the ECG signal it was seen that the low frequency component cause the baseline shift, theses component were deducted to get a signal without baseline drift. Also the high frequency components of the signal were removed for getting denoised signal. A program has been developed with MATLAB software for this work.

References
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  2. Abdel-Rahman, Al-Qawasmi and Khaled Daqrouq: ECG signal enhancement Using Wavelet Transform, Published by WSEAS TRANSACTION on BIOLOGY and BIOMEDICINE; issue: 2; Volume: 7; pp: 62-72; April 2010.
  3. Paul S Addison, The illustrated wavelet transform handbook, (IOP Pub. , 2002).
  4. Daubechies, I. , Ten Lectures on Wavelets, SIAM, Philadelphia, 1992.
  5. A. Grap: An introduction to wavelets, IEEE Computing in science and Engineering, Vol: 2 (2); pp: 50-61, 1995.
  6. Vanisree K and Jyothi Singraraju: Automatic detection of ECG R-R interval using discrete wavelet transform , International Journal on Computer Science and Engineering (IJCSE);Vol:3;No:4;pp:1599-1605;April 4, 2011.
  7. K. Daqrouq: ECG baseline wandering reduction using wavelet transform, Asian journal of information Technology; Vol: 4(11); pp=989-995; 2005.
Index Terms

Computer Science
Information Sciences

Keywords

ECG Wavelet transform P_QRS-T waves Baseline drift Denoising.

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