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http://dx.doi.org/10.9717/kmms.2016.19.3.557

Heart Murmur Detection Algorithm based on Spectral Flatness  

Lee, Yunjung (Institute of Biomedical Engineering Research, Kyungpook National University)
Lee, Gihyoun (Dept. of Medical & Biological Eng., Graduate School, Kyungpook National University)
Na, Sung Dae (Dept. of Medical & Biological Eng., Graduate School, Kyungpook National University)
Seong, Ki Woong (Dept. of Biomedical Eng., Kyungpook National University hospital)
Cho, Jin Ho (School of Electronics Eng., Kyungpook National University)
Kim, Myoung Nam (Dept. of Biomedical Eng., School of Medicine, Kyungpook National University)
Publication Information
Journal of Korea Multimedia Society / v.19, no.3, 2016 , pp. 557-566 More about this Journal
Abstract
Heart sounds generated by the beating heart and blood flow reflect the turbulence created when the heart valves snap shut. Cardiac diagnosis is typically started by an auscultation using a stethoscope, from which a medical doctor, depending on his hearing capabilities and training, listens and interprets the acoustic signal. This method of diagnostic is uncertain, mostly due to the fact that human ear loses the acoustic frequency sensitivity through the years. Even though an auscultation has some weaknesses like uncertainty, it is considered as a primary tool due to its simplicity. In this paper, heart murmur detection algorithm is proposed using time and frequency characteristics of heart sound. The propose heart murmur detection method adapted conventional primary heart sound detection method in time domain and modified spectral flatness method in frequency domain for detecting heart murmurs. From experimental results, it is confirmed that the proposed algorithm detect the heart murmurs efficiently.
Keywords
Heart Sound; Heart Murmur Detection; Cardiac Diagnosis; Spectral Flatness;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 J.S. Choi, Heart Sounds and Murmurs, Hyunmoon, Seoul, 1989.
2 J.E. Guillermo, L.J.R. Castellanos, E.N. Sanchez, and A.Y. Alanis, “Detection of Heart Murmurs Based on Radial Wavelet Neural Network with Kalman Learning,“ Journal of Neurocomputing, Vol. 164, pp. 307-317, 2015.   DOI
3 Nuno Miguel Tavarses Costa e Silva, Phonocardiogram Noise Detection in Realistic Envrionments, Master Thesis of Faculdade de Ciências da Universidade do Porto, 2012.
4 C. Yao, A Study on Heart Sound Signal Analysis and Feature Extraction Methods, Master Thesis of Cheongju University, 2011.
5 G.H. Lee, Y.J. Lee, and M.N. Kim, “Heart Valve Stenosis Region Detection Algorithm on Heart Sounds,“ Journal of Korea Multimedia Society, Vol. 15, No. 11, pp. 1330-1340, 2012.   DOI
6 J.G. Webster, Medical Instrumentation Application and Design 3rd edition, John Wiley & Sons, New York, 1998.
7 Y.J. Lee, P.U. Kim, J.H. Cho, Y.M. Chang, and M.N. Kim, “Single- Channel Adaptive Noise Canceller for Heart Sound Enhancement during Auscultation,“ IEICE Transactions on Information and Systems, Vol. E98-D, No. 10, pp. 2593-2596, 2012.   DOI
8 D. Kumar, P. Carvalho, M. Antunes, R.P. Paiva, and J, Henriques, "Heart Murmur Classification with Feature Selection," Proceeding of International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 4566-4569, 2010.
9 Advanced Physical Diagnosis Learning and Teaching at the Bedside, http://depts.washington. edu/ physdx/heart/tech.html, (accessed Oct., 16, 2015).
10 E.M. Brown, T.S. Leung, W.B. Collis, and A.P. Salmon, Heart Sounds Made Easy 2e, Churchill Livingstone Elsevier, Philadelphia, 2008.
11 B.W. Kim, H.W. Yoon, O,K, Lee, and S.C. Choi, New Clinical Physiology, Korea Medical Book Publisher, Seoul, 2012.