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Evaluation of monofractal and multifractal properties of inter-beat (R-R) intervals in cardiac signals for differentiation between the normal and pathology classes

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IET Wireless Sensor Systems

Micro & Nano Letters

The Journal of Engineering

Evaluation of monofractal and multifractal properties of inter-beat (R-R) intervals in cardiac signals for differentiation between the normal and pathology classes

Content Provider	IET Digital Library
Author	Gorshkov, Oleg Ombao, Hernando
Abstract	In this study, the monofractal and multifractal properties of inter-beat (R-R) intervals in cardiac signals for normal and pathology classes were studied and applied to a dataset in PhysioNet which consists of 24 h R-R intervals from 54 healthy subjects (hs) and 92 patients with various diagnoses [44 with congestive heart failure (chf), 25 with atrial fibrillation (af) and 23 diagnosed with sudden death syndrome (sd)]. The results in this study indicate that the most suitable method for estimating the monofractal properties of R-R intervals is detrending moving average (DMA). The Hurst exponents ( H ) of the healthy and pathological groups, calculated using the DMA method, are shown to be statistically different by the Kruskal–Wallis test [p-value < 0.01; healthy H hs = 0.23(0.18–0.27); pathological group H chf = 0.06(0.03–0.10), H af = 0.05(0.03–0.07), H sd = 0.05(0.03–0.08)]. To study the multifractal properties of R-R intervals, the multifractal detrended fluctuation analysis was used. Formal statistical tests indicate statistically significant differences (p-value < 0.05, ANOVA and pairwise testing) between the width of the spectrum of the chf group W chf = 1.11 ± 0.12 and the width of the spectra of the af group W af = 0.58 ± 0.15, the sd group W sd = 0.60 ± 0.20, and the hs group W hs = 0.61 ± 0.08. Using these results, a logistic regression model was developed for differentiating chf from other pathologies (af and sd).
Starting Page	798
Ending Page	805
Page Count	8
ISSN	17519675
Volume Number	13
e-ISSN	17519683
Issue Number	Issue 9, Dec (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/13/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2018.5536
Journal	IET Signal Processing
Publisher Date	2019-09-10
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Atrial Fibrillation Bioelectric Signal Biology And Medical Computing Cardiac Signal Congestive Heart Failure Digital Signal Processing DMA Method Electrical Activity in Neurophysiological Processes Electrocardiogram Electrocardiography Electrodiagnostics And Other Electrical Measurement Technique Fluctuations Formal Statistical Tests Fractals Healthy Groups Interbeat Intervals Kruskal-Wallis Test Logistic Regression Model Medical Disorders Medical Signal Processing Monofractal Property Multifractal Detrended Fluctuation Analysis Multifractal Property Pathological Groups Probability Theory Regression Analysis Signal Processing And Detection Statistical Testing Statistics Stochastic Linearised SCUC Sudden Death Syndrome
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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