Call for Paper - November 2022 Edition
IJCA solicits original research papers for the November 2022 Edition. Last date of manuscript submission is October 20, 2022. Read More

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

Print
PDF
International Journal of Computer Applications
© 2014 by IJCA Journal
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 and Yahea S M Mahbub. Article: Baseline Drift Removal and De-Noising of the ECG Signal using Wavelet Transform. International Journal of Computer Applications 95(16):15-17, June 2014. Full text available. BibTeX

@article{key:article,
	author = {Iffat Ara and Md. Najmul Hossain and S. M. Yahea Mahbub},
	title = {Article: Baseline Drift Removal and De-Noising of the ECG Signal using Wavelet Transform},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {95},
	number = {16},
	pages = {15-17},
	month = {June},
	note = {Full text available}
}

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

  • L. Cromwell, F. J. Weibell, and E. A. Pfeiffer: Biomedical Instrumentation and Measurements, Prentice Hall of India, New Delhi 2005.
  • 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.
  • Paul S Addison, The illustrated wavelet transform handbook, (IOP Pub. , 2002).
  • Daubechies, I. , Ten Lectures on Wavelets, SIAM, Philadelphia, 1992.
  • A. Grap: An introduction to wavelets, IEEE Computing in science and Engineering, Vol: 2 (2); pp: 50-61, 1995.
  • 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.
  • K. Daqrouq: ECG baseline wandering reduction using wavelet transform, Asian journal of information Technology; Vol: 4(11); pp=989-995; 2005.