Unravelling the potential of phase portrait in the auscultation of mitral valve dysfunctionSwapna Mohanachandran Nair Sindhu
, SREEJYOTHI S
, RENJINI A
, RAJ VIMAL
, SANKARARAMAN SANKARANARAYANA IYER
, 2021, original scientific article
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 dysfunctioninduced 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.
Keywords: phase portrait, auscultation, mitral valve dysfunction, heart murmur, nonlinear time series analysis
Published in RUNG: 28.06.2022; Views: 503; Downloads: 0
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