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Unravelling the potential of phase portrait in the auscultation of mitral valve dysfunction

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Abstract

The manuscript elucidates the potential of phase portrait, fast Fourier transform, wavelet, and time-series analyses of the heart murmur (HM) of normal (healthy) and mitral regurgitation (MR) in the diagnosis of valve-related cardiovascular diseases. The temporal evolution study of phase portrait and the entropy analyses of HM unveil the valve dysfunction-induced haemodynamics. A tenfold increase in sample entropy in MR from that of normal indicates the valve dysfunction. The occurrence of a large number of frequency components between lub and dub in MR, compared to the normal, is substantiated through the spectral analyses. The machine learning techniques, K-nearest neighbour, support vector machine, and principal component analyses give 100% predictive accuracy. Thus, the study suggests a surrogate method of auscultation of HM that can be employed cost-effectively in rural health centres.

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Author notes

  1. M. S. Swapna, S. Sreejyothi, A. Renjini, and Vimal Raj are first authors.

Authors and Affiliations

  1. Department of Optoelectronics, University of Kerala, Trivandrum, Kerala, 695581, India

    M. S. Swapna, S. Sreejyothi, A. Renjini, Vimal Raj & S. Sankararaman

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  1. M. S. Swapna
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  2. S. Sreejyothi
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  3. A. Renjini
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  5. S. Sankararaman
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Correspondence to S. Sankararaman.

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Swapna, M.S., Sreejyothi, S., Renjini, A. et al. Unravelling the potential of phase portrait in the auscultation of mitral valve dysfunction. Eur. Phys. J. Plus 136, 184 (2021). https://doi.org/10.1140/epjp/s13360-021-01185-6

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