Multifractal‐Multiscale Analysis of Cardiovascular Signals: A DFA‐Based Characterization of Blood Pressure and Heart‐Rate Complexity by Gender

Abstract

Detrended Fluctuation Analysis (DFA) is a popular method for assessing the fractal characteristics of biosignals, recently adapted for evaluating the heart-rate multifractal and/or multiscale characteristics. However, the existing methods do not consider the beat-by-beat sampling of heart rate and have relatively low scale resolutions and were not applied to cardiovascular signals other than heart rate. Therefore, aim of this work is to present a DFA-based method for joint multifractal/multiscale analysis designed to address the above critical points and to provide the first description of the multifractal/multiscale structure of interbeat intervals (IBI), systolic blood pressure (SBP), and diastolic blood pressure (DBP) in male and female volunteers separately. The method optimizes data splitting in blocks to reduce the DFA estimation variance and to evaluate scale coefficients with Taylor's expansion formulas and maps the scales from beat domains to temporal domains. Applied to cardiovascular signals recorded in 42 female and 42 male volunteers, it showed that scale coefficients and degree of multifractality depend on the temporal scale, with marked differences between IBI, SBP, and DBP and with significant sex differences. Results may be interpreted considering the distinct physiological mechanisms regulating heart-rate and blood-pressure dynamics and the different autonomic profile of males and females.

Entropy in Heart Rate Dynamics Reflects How HRV-Biofeedback Training Improves Neurovisceral Complexity during Stress-Cognition Interactions

“…While we use RCMSE here, a large panel of complexity-based methods for analyzing interbeat time series can be drawn. To evoke a few representative examples, sample entropy has been applied to wavelet-based decomposition in very-low (VLF), low (LF), and high-frequencies (HF) at different ages [ 54 ]; multiscale entropy has been applied to diurnal vs. nocturnal series at different ages and health status [ 45 ]; the monofractal scaling exponent has been shown to change with ageing, cardiac health, and disease [ 55 , 56 ]; multifractality disruption has been evidenced in heart failure [ 57 ]; and, more recently, multifractility-multiscale analysis of both cardiac and vascular dynamics provided a deeper understanding of sexual dymorphism in autonomic control of heart and peripheral vascular districts [ 58 ]. In each case, the added value of obtaining complexity metrics was highlighted.…”

The Heart Rate Variability Multifractality Spectrum and not the Power Spectrum is Altered in Paraplegic Individuals With Low-Level Lesion

“…The multifractal-multiscale DFA was performed on the beat-by-beat RRI series. To minimize the estimation variability of F q (n), the equation 1 was calculated splitting the series into maximally overlapped blocks of size n, as described in [9]. The multifractal variability function, F q (n), was estimated for a set of scales, n k , with k between 1 and K, equispaced over the logarithmic scale.…”

Investigation of the Implications of “Haze Special Law” on Air Quality in South Korea

“…Moreover, MF-DFA is also an efficient method in analyzing the human heart rate time series [21]. Based on the analysis of blood pressure and heart-rate complexity, Gender Castiglioni et al [22] used the multifractal technique to investigate cardiovascular warning signals. Moreover, MF-DFA has been used in some studies to implement specific image analysis [23,24].…”