Day and Night Changes of Cardiovascular Complexity: A Multi-Fractal Multi-Scale Analysis

Abstract

Recently, a multifractal-multiscale approach to detrended fluctuation analysis (DFA) was proposed to evaluate the cardiovascular fractal dynamics providing a surface of self-similarity coefficients α(q,τ), function of the scale τ, and moment order q. We hypothesize that this versatile DFA approach may reflect the cardiocirculatory adaptations in complexity and nonlinearity occurring during the day/night cycle. Our aim is, therefore, to quantify how α(q, τ) surfaces of cardiovascular series differ between daytime and night-time. We estimated α(q,τ) with −5 ≤ q ≤ 5 and 8 ≤ τ ≤ 2048 s for heart rate and blood pressure beat-to-beat series over periods of few hours during daytime wake and night-time sleep in 14 healthy participants. From the α(q,τ) surfaces, we estimated short-term (<16 s) and long-term (from 16 to 512 s) multifractal coefficients. Generating phase-shuffled surrogate series, we evaluated short-term and long-term indices of nonlinearity for each q. We found a long-term night/day modulation of α(q,τ) between 128 and 256 s affecting heart rate and blood pressure similarly, and multifractal short-term modulations at q < 0 for the heart rate and at q > 0 for the blood pressure. Consistent nonlinearity appeared at the shorter scales at night excluding q = 2. Long-term circadian modulations of the heart rate DFA were previously associated with the cardiac vulnerability period and our results may improve the risk stratification indicating the more relevant α(q,τ) area reflecting this rhythm. Furthermore, nonlinear components in the nocturnal α(q,τ) at q ≠ 2 suggest that DFA may effectively integrate the linear spectral information with complexity-domain information, possibly improving the monitoring of cardiac interventions and protocols of rehabilitation medicine.

A Single Session of SMR-Neurofeedback Training Improves Selective Attention Emerging from a Dynamic Structuring of Brain–Heart Interplay

“…, which is quite similar to the alpha short-term coefficient reported by [ 47 ], to , but takes into account the excessive deviations introduced by the method in alpha values at the shortest scales, typically [ 26 , 28 ].…”

Multiscale assessment of the degree of multifractality for physiological time series

“…As an application on real biomedical signals, we considered the same 24 h blood pressure recordings in healthy participants of a previous study that demonstrated differences between daytime and night-time in the α(q, n) coefficients of the heart rate [12]. Therefore, the α CF (n) index proposed in the present work could clarify whether the previously observed differences regard not only the value of the coefficients but also the degree of multifractality.…”

“…Each pulse wave was identified on the blood pressure signal sampled at 170 Hz, artefacts and premature beats were removed, and the series of inter-beat intervals (IBI) was derived beat by beat. Details on the participants and signal acquisition and preelaboration are provided in [12]. In each IBI series, we selected two segments of N ≥ 14 000 beats, in the afternoon ('Day' period) and after 23.00 ('Night' period), and calculated F q (n) as in equation ( 2.3) for 6 < n < N/4 beats, −5 ≤ q ≤ + 5, with detrending polynomials of order 1 and 2.…”

“…This suggested combining the two approaches to obtain a multifractal-multiscale representation of DFA coefficients, α(q, n) [8]. The bidimensional surface of coefficients revealed an unexpected richness of details in the self-similarity structure of the cardiovascular signals [9][10][11][12]. In particular, the α(q, n) surfaces may indicate the scales where the dynamics are monofractal and where they are multifractal, or where clinical treatments, physiological conditions and manoeuvres affect the degree of multifractality.…”

Assessing Complexity in Physiological Systems through Biomedical Signals Analysis

“…Results support the hypothesis of cardiovascular self-organized criticality and provide evidence of a different distribution of bradycardic sequences in the participants who experienced syncope symptoms during the test. Furthermore, cardiovascular multifractality is the topic of the paper by Castiglioni et al [ 12 ] that quantifies the multifractal–multiscale structure of the heart-rate and blood-pressure series, revealing night/day modulations of nonlinear fractal components at specific temporal scales. The work suggests that the multifractal–multiscale approach improves the clinical value of the 24 h analysis of blood pressure and heart rate variability.…”