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Signal Processing and Extensive Characterization Method of Heart Sounds Based on Wavelet Analysis

Rimuljo Hendradi(1*), Achmad Arifin(2), Hiro Shida(3), Suhendar Gunawan(4), Mauridhi Hery Purnomo(5), Hideyuki Hasegawa(6), Hiroshi Kanai(7)

(1) Graduate Program of Electrical Engineering, Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Indonesia
(2) Graduate Program of Electrical Engineering, Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Indonesia
(3) Graduate Schools of Engineering and Biomedical Engineering, Tohoku University, Japan
(4) Kebonjati Hospital, Indonesia
(5) Graduate Program of Electrical Engineering, Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Indonesia
(6) Graduate School of Science and Engineering for Research, University of Toyama, Japan
(7) Graduate Schools of Engineering and Biomedical Engineering, Tohoku University, Japan
(*) Corresponding author


DOI: https://doi.org/10.15866/iree.v11i1.8138

Abstract


One of the valuable methods of cardiac valve diagnosis can be performed by auscultation. We proposed a signal processing and extensive characterization method based on wavelet analysis to investigate important characteristics of heart sounds of normal and pathologic systolic murmur human subjects. Time-scale maps yielded by wavelet transform calculation were solved using magnitude thresholding operation and centre of gravity to restrict temporal and frequency-related of valvular activities. From our experimental results, temporal and frequency-related parameters of S1, S2, and their components could be characterized precisely. Application of our method was adequate to characterize the heart sounds objectively, clearly, systematically, and comprehensively. The method was considered valuable to explain mechanisms of cardiac valves functions. We expected that the method would be helpful for clinical diagnosis as well as developing of heart sound modelling and educational purpose. Next topic of our study was addressed for classification of the heart sounds.
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Keywords


Centre of Gravity; Heart Sound; Thresholding Method; Wavelet Transform

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References


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