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.
De Santis, Enrico; Naraei, Parisa; Martino, Alessio; Sadeghian, Alireza; Rizzi, Antonello. (2022). Multifractal Characterization and Modeling of Blood Pressure Signals. ALGORITHMS, (ISSN: 1999-4893), 15:8, 1-17. Doi: 10.3390/a15080259.
Multifractal Characterization and Modeling of Blood Pressure Signals
Alessio Martino
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2022
Abstract
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.| File | Dimensione | Formato | |
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