HYBRID CLASSIFICATION SCHEMES FOR HEART MURMUR DETECTION TO ASSIST PHONOCARDIOGRAM BASED SIGNAL ACQUISITION

Authors

  • A.D. Jeyarani Professor, AnnaSaheb Dange College of Engineering & Technology, Maharashtra
  • Reena Daphne Assistant Professor, in Nagercoil, Tamil Nadu
  • Solomon Roach Research Scholar, Anna University, Chennai

DOI:

https://doi.org/10.24297/jac.v13i9.5803

Keywords:

Neural Network, Phonocardiogram, Classifier

Abstract

The main contribution of this paper has been to introduce nonlinear classification techniques to extract more information from the PCG signal. Especially, Artificial Neural Network classification techniques have been used to reconstruct the underlying system’s state space based on the measured PCG signal. This processing step provides a geometrical interpretation of the dynamics of the signal, whose structure can be utilized for both system characterization and classification as well as for signal processing tasks such as detection and prediction.

Downloads

Download data is not yet available.

Author Biographies

A.D. Jeyarani, Professor, AnnaSaheb Dange College of Engineering & Technology, Maharashtra

Department of Electronics and Telecommunication Engineering

Reena Daphne, Assistant Professor, in Nagercoil, Tamil Nadu

Department of Electrical and Electronics, Stella Mary’s College of Engineering,

Solomon Roach, Research Scholar, Anna University, Chennai

Department of Information and Communication Engineering,

References

[1] S.M. DEBBAL, F.BEREKSI-REGUIG, “Frequency analysis of the heartbeat sounds”, Biomedical Soft Computing and Human Sciences, Vol.13, No.1, pp.85-90 (2008).
[2] TanveerSyeda-Mahmood, FeiWang, “Shape-based Retrieval of Heart Sounds for Disease Similarity Detection”, San Jose.
[3] SreeramanRajan, RajamaniDoraiswami, Raymond Watrous, “Wavelet Based Bank Of Correlators Approach for Phonocardiogram Signal Classification”, 1998 IEEE.
[4] Hideaki Shino, Hisashi Yoshida, Kazuo YanaKensuke Harada, JiroSudoh, and EishiHarasawa, “Detection and Classification of Systolic Murmur for Phonocardiogram Screening”, 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Amsterdam 1996.
[5] Haibin Wang, Jian Chen and Yuliang Hu, Zhongwei Jiang and Choi Samjin, “Heart Sound Measurement and Analysis System with Digital Stethoscope”, 2009 IEEE.
[6] Qiong Li, Jing.Wu, Xin He, “Content-based Audio Retrieval using Perceptual Hash”, International Conference on Intelligent Information Hiding and Multimedia Signal Processing.
[7] M. SabarimalaiManikandan and S. Dandapat, “Wavelet-Based ECG and PCG Signals Compression Technique for MobileTelemedicine”, 15th International Conference on Advanced Computing and Communications.
[8] H Liang, S Lukkarinen, I Hartimo, “Heart Sound Segmentation Algorithm Based on Heart Sound Envelolgram”, Computers Cardiology 1997 Vol24.
[9] S. Kiranyaz and M. Gabbouj, “Generic content-based audio indexing and retrievalFramework”, IEE Proc.-Vis. Image Signal Process., Vol. 153, No. 3, June 2006 285.
[10] Wenjie Fu, Xinghai Yang, Yutai Wang, “Heart Sound Diagnosis Based on DTW and MFCC”, 2010 3rd International Congress on Image and Signal Processing (CISP2010).
[11] J S D Mason and Y Gu, “Perceptually-Based Features in ASR”
[12] P.R. White, W.B. Collis and A.P. Salmon, “Analyzing Heart Murmurs Using Time-Frequency Method”, ISVR, University of Southampton, High field, Hants, U.K.
[13] Zeeshan Syed, Daniel Leeds, Dorothy Curtis, Francesca Nesta, Robert A. Levine, and John Guttag, “A Framework for the Analysis of Acoustical Cardiac Signals”, IEEE Transactions on Biomedical Engineering, Vol. 54, No. 4, April 2007.
[14] Emil Jovanov, Kristen Wegner, Vlada Radivojevic, Dusan Starcevic, Martin S. Quinn, and D. B. Karron, “Tactical Audio and Acoustic Rendering in Biomedical Applications”, IEEE Transactions on Information Technology in Biomedicine, Vol. 3, No. 2, June 1999.
[15] Lie Lu, Hong-Jiang Zhang, and Hao Jiang, “Content Analysis for Audio Classification and Segmentation”, Senior Member, IEEE, IEEE Transactions on Speech and Audio Processing, Vol. 10, No. 7, October 2002.
[16] Robert A. Dennis and Sanjiv S. Gambhir, “Internet Question and Answer (iQ&A): A Web-Based Survey Technology”, IEEE Transactions On Information Technology In Biomedicine, VOL. 4, NO. 2, June 2000.
[17] Dimitar H. Stefanov, Zeungnam Bien, Won-Chul Bang, “The Smart House for Older Persons and Persons With Physical Disabilities: Structure, Technology Arrangements, and Perspectives”, Senior Member, IEEE, Member, IEEE, IEEE Transactions On Neural Systems And Rehabilitation Engineering, VOL. 12, NO. 2, June 2004
[18] Yasemin M. Akay, Metin Akay, WalterWelkowitz, John L. Semmlow, and John B. Kostis, “Noninvasive Acoustical Detection of Coronary Artery Disease: A Comparative Study of Signal Processing Methods”, Student Member. IEEE, Senior Member, IEEE, Fellow, IEEE, IEEE Transactions on Biomedical Engineering. Vol. 40, No. 6, June 1993.
[19] Frank Baumgarte, “Improved Audio Coding Using a Psychoacoustic Model Based on a Cochlear Filter Bank”, IEEE Transactions On Speech And Audio Processing, VOL. 10, NO. 7, October 2002.
[20] Jesper Jensen, Richard Heusdens, and Soren Holdt Jensen, “A Perceptual Subspace Approach for Modeling of Speech and Audio Signals with Damped Sinusoids”, Member, IEEE and Senior Member, Senior Member, IEEE Transactions On Speech And Audio Processing, Vol. 12, No. 2, March 2004.

Additional Files

Published

2017-02-22

How to Cite

Jeyarani, A., Daphne, R., & Roach, S. (2017). HYBRID CLASSIFICATION SCHEMES FOR HEART MURMUR DETECTION TO ASSIST PHONOCARDIOGRAM BASED SIGNAL ACQUISITION. JOURNAL OF ADVANCES IN CHEMISTRY, 13(9), 6480–6488. https://doi.org/10.24297/jac.v13i9.5803

Issue

Vol. 13 No. 9 (2017)

Section

Articles

License

Creative Commons License All articles published in Journal of Advances in Linguistics are licensed under a Creative Commons Attribution 4.0 International License.