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Analysis of PCG Signals Using Daubechies Wavelet Family

ANITA DEVI*, Abhishek Misal**, G. R. Sinha***

* Assistant Professor and Research Scholar, Department of Electronics & Tele., Chhatrapati Shivaji Institute of Technology, Durg, India.

** Sr. Assistant Professor and Research Scholar, Department of Electronics & Tele., Chhatrapati Shivaji Institute of Technology, Durg, India.

*** Professor and Associate Director, Faculty of Engineering & Technology, Shri Shankaracharya Technical Campus, Bhilai, India.

Periodicity:February - April'2013
DOI : https://doi.org/10.26634/jcs.2.2.2243

Abstract

The authors have analyzed a Bio-medical system for normal and abnormal heart sound identification based using Discrete Wavelet Transform (DWT) which is very useful in diagnosis of heart diseases. Due to the presence of sampling frequency components, the wavelets have a different decomposition level and therefore for better performance for a particular heart sound, DWT (Daubechies family) is applied up to 10 levels to extract the features for the individual heart signal. One dimensional feature extraction is obtained by evaluating the search parameters such as maximum energy, maximum variance, maximum entropy, and the analysis using these parameters provide best wavelet for determining suitable features of phonocardiaogram (PCG) signals.

Keywords

Electrocardiogram(ECG), Phonocardiogram (PCG), Aortic stenosis (AS), Aortic regurgitation (AR), Mitral stenosis (MS), Mitral r (MR), Discrete wavelet transform (DWT), Normal heart sound (NHS)

How to Cite this Article?

Tiwari, A. D., Misal, A. and Sinha, G. R. (2013). Analysis Of PCG Signals Using Daubechies Wavelet Family. i-manager’s Journal on Communication Engineering and Systems, 2(2), 23-29. https://doi.org/10.26634/jcs.2.2.2243

References

[1]. Santos, M.A.R. & Souza,M.N. (2001). Detection of first and second cardiac sounds based on time frequency analysis, Proceedings of the 23rd Annual EMBS International Conference, October 25-28, Istanbul, Turkey.

[2]. Say, O., Dokur, Z. & Olmez, T. (2002). Classification of heart sounds by using wavelet transform, Proceedings of the 2nd Annual International Conference of the IEEE-EMBS, pp.128-129.

[3]. Debbal, S.R. & Bereksi-Reguig, F. (2008). Computerized heart sounds analysis, Computers in Biology and Medicine, Vol. 38, pp. 263-280.

[4]. Debbal, S.R., Agzarian, J. & Abbott, D. (2001). Optimal wavelet denoising for phonocardiograms, Microelectronics Journal, Vol. 32, pp. 931-941.

[5]. Martinez, A.J. & Ruiz-Merino, R. (2004). Wavelet and wavelet packet compression of phonocardiogram's, Electronics Letters, Vol. 40, pp. 1040-1041.

[6]. Harun Uguz (2012). Adaptive Neuro-fuzzy Inference System for Diagnosis of the Heart Valve Diseases Using Wavelet Transform with Entropy, Neural Computing and Applications, Springer-verlag London Limited, pp. 1617–1628.

[7]. Misal, A., Sinha, G.R., Potdar, R.M. & Kowar, M.K. (2012). Comparison of Wavelet Transforms For Denoising And Analysis of PCG Signal, i-manager's Journal on Communication Engineering and Systems, Vol. 1 , No. 1, pp. 49-53.

[8]. Misal, A. & Sinha, G.R. (2012). Separation of Lung Sound from PCG Signals Using Wavelet Transform, Journal of Basic and Applied Physics, Vol. 1, Iss. 2, pp. 57-61.

[9]. Anita Devi & Misal,A. (2013). A Survey on Classifiers Used in Heart Valve Disease Detection, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 2, Issue 1, pp. 234-240.

[10]. Misal, A. & Sinha, G.R. (2012). Denoising Of PCG Signal by Using Wavelet Transforms, Advances in Computational Research, Vol. 1, Issue 1, pp. 467-472.

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Analysis of PCG Signals Using Daubechies Wavelet Family

Abstract

Keywords

How to Cite this Article?

References

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