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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 12, 2021.
Abstract: The analysis of heart rate variability is based on the intervals between the successive heartbeats and thanks to it information about the functional state of the person can be obtained and the dynamics of its change can be traced. The nonlinear dynamics methods provide additional, prognostic information about the patient's health, complementing traditional analyses and are considered potentially promising tools for assessing heart rate variability. In this article, studies have been carried out to identify the mono- and multifractal properties of two groups of people: healthy controls and patients with arrhythmia using Wavelet Transform Modulas Maxima Method. The obtained results from the studies show that for healthy subjects the multifractal spectrum is broader than the spectrum of patients with arrhythmia. The value of the Hurst exponent is lower in healthy controls, and in patients with arrhythmia this parameter tends to one. For the healthy subjects, the scaling exponent showed nonlinear behaviour, while for patients with arrhythmia it was linear. This indicates that heart rate variability in healthy controls has multifractal behaviour while patients with arrhythmia have monofractal behaviour. The finding may be useful in diagnosing subjects with cardiovascular disease, as well as in predicting future diseases, as the heart rate variability changes at the slightest deviation in the health status of subjects before the onset of relevant signs of the disease.
Evgeniya Gospodinova, Galya Georgieva-Tsaneva and Penio Lebamovski, “Multifractal Analysis of Heart Rate Variability by Applying Wavelet Transform Modulas Maxima Method” International Journal of Advanced Computer Science and Applications(IJACSA), 12(12), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0121203
@article{Gospodinova2021,
title = {Multifractal Analysis of Heart Rate Variability by Applying Wavelet Transform Modulas Maxima Method},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0121203},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0121203},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {12},
author = {Evgeniya Gospodinova and Galya Georgieva-Tsaneva and Penio Lebamovski}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.