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