Mohanachandran Nair Sindhu Swapna (Avtor), S. Sreejyoth (Avtor), A. Renjini (Avtor), Vimal Raj (Avtor), Sankaranarayana Iyer Sankararaman (Avtor)

Povzetek

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.

Ključne besede

phase portrait;auscultation;mitral valve dysfunction;heart murmur;nonlinear time series analysis;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UNG - Univerza v Novi Gorici
UDK: 53
COBISS: 112992771 Povezava se bo odprla v novem oknu
ISSN: 2190-5444
Št. ogledov: 503
Št. prenosov: 0
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

URN: URN:SI:UNG
Vrsta dela (COBISS): Delo ni kategorizirano
Strani: str. 1-15
Letnik: ǂVol. ǂ136
Zvezek: ǂiss. ǂ2
Čas izdaje: 2021
DOI: 10.1140/epjp/s13360-021-01185-6
ID: 15766872