CFP last date
22 April 2024
Reseach Article

Heart Sounds Classification using Feature Extraction of Phonocardiography Signal

by Mandeep Singh, Amandeep Cheema
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 77 - Number 4
Year of Publication: 2013
Authors: Mandeep Singh, Amandeep Cheema
10.5120/13381-1001

Mandeep Singh, Amandeep Cheema . Heart Sounds Classification using Feature Extraction of Phonocardiography Signal. International Journal of Computer Applications. 77, 4 ( September 2013), 13-17. DOI=10.5120/13381-1001

@article{ 10.5120/13381-1001,
author = { Mandeep Singh, Amandeep Cheema },
title = { Heart Sounds Classification using Feature Extraction of Phonocardiography Signal },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 77 },
number = { 4 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 13-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume77/number4/13381-1001/ },
doi = { 10.5120/13381-1001 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:49:21.897267+05:30
%A Mandeep Singh
%A Amandeep Cheema
%T Heart Sounds Classification using Feature Extraction of Phonocardiography Signal
%J International Journal of Computer Applications
%@ 0975-8887
%V 77
%N 4
%P 13-17
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Phonocardiogram (PCG) signals contain very useful information about the condition of the heart. By analyzing these signals, early detection and diagnosis of heart diseases can be done. It is also very useful in the case of infants, where ECG recording and other techniques are difficult to implement. In this paper, a classification method is proposed to classify normal and abnormal heart sound signals having murmurs without getting into the cumbersome process of segmenting fundamental heart sounds (FHS) using Electrocardiogram (ECG) gating. The proposed algorithm can be easily implemented on latest electronic stethoscopes, and therefore the unnecessary ECG can be avoided.

References
  1. Roy, D. , Sargeant, J. , Gray, J. , Adn, B. , Allen, M. , and Fleming, M. 2002. Helping family physicians improve their cardiac auscultation skills. Journal of Continuing Education in the Health Professions 22. 152–159.
  2. Babaei, S. , and Geranmayeh, A. 2009. Heart Sound reproduction based on neural network classification of cardiac valve disorders using wavelet transforms of PCG signals. Elsevier. Computers in Biology and Medicine 39. 8-15.
  3. Kagawa, Y. , Sato, N. , Nitta, S. , Saji, K. , Tanaka, M. , Shlbota, Y. , and Horiuchi, T. 1977. Sound Soectroanalvtic Diagnosis of Malfunctionning Prosthetic Valves. Tokohu J. Exp. Med. , 123. 77-89.
  4. Durand, L. , Blanchard, M. , Sabbah, H. , Hamid, M. , Kemp S. , and Stein, P. 1988. A Bayes model for automatic detection and quantification of bioprosthetic valve degeneration. Mathematical and Computer Modelling, Vol. 11. 158-163.
  5. Barschdor, D. , Femmer, U. , and Trowitzsch, E. 1995. Automatic phonocardiogram signal analysis in infants based on wavelet transforms and artificial neural networks. Computers in Cardiology. IEEE, Vienna, Austria. 753–756.
  6. Asir, B. , Khadra, L. , Abbasi, A. , and Mohammed, M. 1996. Time–frequency analysis of heart sounds. Proc. of IEEE TENCON Conf. on Dig. Sig. Proc. Appl. , vol. 2, Perth, WA, Australia. 553–558.
  7. Asir, B. , Khadra, L. , Abbasi A. , and Mohammed, M. 1996. Multiresolution analysis of heart sounds. Proceedings of the Third IEEE Internationall Conf. on Elec. , Circ. , and Sys. , vol. 2, Rodos, Greece. 1084–1087.
  8. Lee, J. , Lee, S. , Kim, I. , Min, H. , and Hong, S. 1999. Comparison between short time Fourier and wavelet transform for feature extraction of heart sound. Proceedings of IEEE TENCON 99, vol. 2, Cheju Island, South Korea. 1547–1550.
  9. Shino, H. , Yoshida, H. , Mizuta H. , and Yana, K. 1997. Phonocardiogram classification using time–frequency representation. Proc. of the 19th International Conf. of the IEEE Eng. in Med. and Biol. Soc. , vol. 4, Chicago, IL. 1636–1637.
  10. Rangayyan, R. , and Lehner, R. 1988. Phonocardiogram Signal Analysis: A Review. CRC Critical Reviews in Biomedical Engineering, 15(3). 211-236.
  11. Muruganantham. 2003. Methods for Classification of Phonocardiogram. TENCON.
  12. Shui, L. 2004. AM13 Analysis of Heart Sound. Thesis. National University of Singapore.
  13. Segaier, M. , Lilja, O. , Lukkarinen, S. , Ornmo, L. , Sepponen, R. , and Pesonen, E. 2005. Computer-Based Detection and Analysis of Heart Sound and Murmur. Annals of Biomedical Engineering, Vol. 33, No. 7. 937–942.
  14. Jiang, Z. , and Choi, S. 2006. A cardiac sound characteristic waveform method for in-home heart disorder monitoring with electric stethoscope. Expert Systems with Applications 31. 286–298.
  15. Ahlstrom, C. , Liljefelt, O. , Hult P. , and Ask, P. 2005. Processing of the Phonocardiographic Signal, Methods for the Intelligent Stethoscope. Studies in Science and Technology. Thesis No. 1253.
  16. Ahlstrom, C. , Hult, P. , and Ask, P. 2006. Thresholding distance plots using true recurrence points. Proceedings of the IEEE Conference on Acoustics, Speech and Signal Processing.
  17. Noponen, A. , Lukkarinen, S. , Angerla, A. , and Sepponen, R. 2007. Phono-spectrographic analysis of heart murmur in children. BMC Pediatrics.
  18. Amit, G. , Gavriely, N. , and Intrator, N. 2009. Cluster analysis and Classification of Heart Sounds. Elsevier, Biomedical Signal Processing and Control 4. 26-36.
  19. Maglogiannis, I. , Loukis, E. , Zafiropoulos, E. , and Statis, A. Support Vector Machine-based identification of heart valve diseases using Heart Sounds. Elsevier. Computer methods and programs in Biomedicine 95. 47-61.
  20. Vishwanath, M. , Shervegar, Bhat, G. , and Shetty, R. 2011. Phonocardiography- the future of cardiac auscultation. International Journal of Scientific & Engineering Research Volume 2, Issue 10.
  21. Bentley, P. , Nordehn, G. , Coimbra, M. , Mannor, S. 2011. The PASCAL Classifying Heart Sounds Challenge 2011. www. peterjbentley. com/heartchallenge/index. html.
  22. Rabiner, L. , and Shafer, R. 2008. 2nd Edition. Digital Processing of Speech Signals. Prentice Hall: New Jersey, USA.
Index Terms

Computer Science
Information Sciences

Keywords

Heart sounds Murmurs Feature extraction Naïve Bayes Bayes Net classifier.