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Multifractal Detrended Fluctuation Analysis of Phonocardiogram signal and classification using Support Vector Machine

Article scientifique 2023 Anglais

Résumé

Abstract The aim of this study is to discover and develop a reliable method to assist doctors in the early detection and diagnosis of heart disease, by analyzing the normal and abnormal Phonocardiogram signal (PCG)by using Multifractal Detrended Fluctuation Analysis (MFDFA) in order to comprehend and explore the underlying dynamics between pathological and normal case, as this method allowed extracting the most important characteristics of the PCG signal and also proved its effectiveness by 98.5075 % when classifying its results in support vector machine (SVM),the proposed method applied at MATLAB R2022b with record signals from PhysioNet and Michigan web site. The MFDFA technique appears to be promising in heart disease study

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Houda, H. (2023). Multifractal Detrended Fluctuation Analysis of Phonocardiogram signal and classification using Support Vector Machine. https://doi.org/10.21203/rs.3.rs-2810058/v1

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Auteur(s)

Hakkoum Khaoula Nour El Houda

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