Algorithms (Jul 2022)

Multifractal Characterization and Modeling of Blood Pressure Signals

  • Enrico De Santis,
  • Parisa Naraei,
  • Alessio Martino,
  • Alireza Sadeghian,
  • Antonello Rizzi

DOI
https://doi.org/10.3390/a15080259
Journal volume & issue
Vol. 15, no. 8
p. 259

Abstract

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In this paper, a multi-fractal analysis on a diastolic blood pressure signal is conducted. The signal is measured in a time span of circa one day through the multifractal detrended fluctuation analysis framework. The analysis is performed on asymptotic timescales where complex regulating mechanisms play a fundamental role in the blood pressure stability. Given a suitable frequency range and after removing non-stationarities, the blood pressure signal shows interesting scaling properties and a pronounced multifractality imputed to long-range correlations. Finally, a binomial multiplicative model is investigated showing how the analyzed signal can be described by a concise multifractal model with only two parameters.

Keywords