The article discusses the characteristics of the fractality of heart rate variability represented by a time series. An algorithm for calculating the Hurst exponent is presented, which allows one to evaluate the degree of chaotization of the signal in question. The capabilities of various multifractal analysis programs are shown, which require the use of different mathematical models.
References
[1]
Bogachev, M.I., Kayumov, A.R., Krasichkov, A.S. and Markelov, O.A. (2012) Mathematical Methods for Identifying Regulatory and Statistical Patterns in Large Volume Biomedical and Economic Data. SPbETU “LETI”, Saint Petersburg, 176 p.
[2]
Nemirko, A.P., Manilo, L.A. and Kalinichenko, A.N. (2017) Mathematical Analysis of Biomedical Signals and Data. Physmatlit, Moscow, 248 p.
[3]
Cronover, R.M. (2006) Fractals and Chaos in Dynamical Systems. Postmarket Publ., Moscow, 488 p.
[4]
Feder, E. (2013) Fractals. Springer Science Business Media, LLC, Berlin, 282 p.
[5]
Vinogradova, A.A. and Trutenko, S.V. (2011) Comparative Features of Multifractal Analysis Programs. News Universities “Instrument Making”, 54, 35-38.
https://doi.org/10.1016/j.dza.2011.04.022
