CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Efficient Use of Bi-orthogonal Wavelet Transform for Cardiac Signals

by Arpit Sharma, Richa Sharma, Sandeep Toshniwal
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 89 - Number 8
Year of Publication: 2014
Authors: Arpit Sharma, Richa Sharma, Sandeep Toshniwal
10.5120/15522-4269

Arpit Sharma, Richa Sharma, Sandeep Toshniwal . Efficient Use of Bi-orthogonal Wavelet Transform for Cardiac Signals. International Journal of Computer Applications. 89, 8 ( March 2014), 19-23. DOI=10.5120/15522-4269

@article{ 10.5120/15522-4269,
author = { Arpit Sharma, Richa Sharma, Sandeep Toshniwal },
title = { Efficient Use of Bi-orthogonal Wavelet Transform for Cardiac Signals },
journal = { International Journal of Computer Applications },
issue_date = { March 2014 },
volume = { 89 },
number = { 8 },
month = { March },
year = { 2014 },
issn = { 0975-8887 },
pages = { 19-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume89/number8/15522-4269/ },
doi = { 10.5120/15522-4269 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:08:42.476513+05:30
%A Arpit Sharma
%A Richa Sharma
%A Sandeep Toshniwal
%T Efficient Use of Bi-orthogonal Wavelet Transform for Cardiac Signals
%J International Journal of Computer Applications
%@ 0975-8887
%V 89
%N 8
%P 19-23
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the detection of various cardiac abnormalities the ECG finds its importance. ECG signal de-noising process in an embedded platform is a challenge which has to deal with several issues. Noise reduction in low amplitude ECG signals by various de-noising techniques is an important task of biomedical science. ECG signals are very low frequency signals of about 0. 5Hz-100Hz. There are various types of artifacts which get added in ECG signals and change the original signal features, therefore there is a need of removal of these artifacts from the original ECG signal. The noises that commonly disturb the basic electrocardiogram signal are power line interference (PLI), electrode contact noise, motion artifacts, electromyography (EMG) noise and instrumentation noise. These noises can be classified according to their frequency content. In this paper, the wavelet transform based approach for removing noise is used. In this paper, the discrete wavelet transform (DWT) at level 8 was applied to noisy ECG signals and decomposition of these ECG signals was performed. After removal of noise component using thresholding technique, decomposed signal is again reconstructed using Inverse discrete wavelet transform (IDWT). Here for de-noising the ECG signal, bi-orthogonal wavelet transform is used and the most efficient idea for noise removal process is concluded with this wavelet transform. The simulation has been done in MATLAB environment with the help of SIMULINK. The experiments are carried out on MIT-BIH database. Performance analysis was performed by evaluating Mean Square Error (MSE), Signal-to-noise ratio (SNR), Peak Signal-to-noise ratio (PSNR) and visual inspection over the de-noised signal from each algorithm.

References
  1. Anonymous, ANSI/AAMI EC11-1991, "American National Standard for Diagnostic Electrocardiographic Devices".
  2. Emmanual C. Ifeachor, Barrie W. Jervis: "Digital signal processing, a practical approach, second edition", Moscow: Yillyams(2004).
  3. Y. Der Lin and Y. Hen Hu "Power line interference detection and suppression in ECG signal processing", IEEE Transactions and Biomedical engineering, vol. 55, pp. 354- 357, January, 2008.
  4. N. V Thakor and Y. S. Zhu, "Application of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection", IEEE Transactions and Biomedical Engineering, vol. 38, no. 8, pp. 785- 794, August,1991.
  5. J. M Leski and N. Henzel, "ECG baseline wander and power line interference reduction using nonlinear filter bank", Signal processing, vol. 85, pp. 781-793, 2005.
  6. Mahesh S Chavan, R A Agrawala, M. D. Uplane. "Digital Elliptic Filter Application for noise Reduction in ECG Signal" 4th Wseas International Conference on Electronics, Control & Signal Processing Miami Florida USA 17-19 Nov. 2005 (pg 58-63).
  7. C. Mihov and I Dotsinsky, "Power line Interference elimination from ECG in case of non-multiplicity between the sampling rate and power line frequency", Biomedical Signal processing and control,vol. 3,pp. 334- 340, June ,2008.
  8. B. Natwong, P. Sooraksa, C. Pintavirooj, S. Bunluechokchai, and W. Ussawawongaraya, "Wavelet Entropy Analysis of the High Resolution ECG", ICIEA The 1st IEEE Conference on Industrial Electronics and Applications, May 2006.
  9. S. Gilberto, F. Thomas, R. Lutz, MR. Antoni, M. Markku, B. Klaus, B. Martin, and B. Gnter, "Multi-resolution decomposition of the signal-averaged ECG using the Mallat approach for prediction of arrhythmic events after myocardial infarction", Journal of Electro-cardiology, vol. 29,no. 3, pp. 223-234, 1996.
  10. M. Boutaa, F. Bereksi-Reguig, and S. M. A. Debbal, "ECG signal processing using multi-resolution analysis", Journal of Medical Engineering &Technology, vol. 32, no. 6, pp. 466-478, November/December 2008.
  11. Donoho DL, Johnstone IM(1994). "Ideal spatial adaptation by wavelet shrinkage", Biometrika, Vol. 81, No. 3, pp. 425-455.
  12. Donoho DL(1995). "De-noising by soft-thresholding", IEEE Trans Inform Theory, Vol. 14, No. 3,pp. 612-627.
  13. Mahmoodabadi and S. Ahmadian, "ECG feature extraction based on multi-resolution wavelet transform", Proceedings of the IEEE 27th Annual Conference on Engineering in Medicine and Biology, pp. 3902–3905, Shanghai, China, January 2005.
Index Terms

Computer Science
Information Sciences

Keywords

ECG Wavelet Transform Discrete Wavelet Transform MSE PSNR.

Powered by PhDFocusTM