multiscale detrended fluctuation analysis

This study explores the efficacy of various EEG complexity measures in detecting mind wandering during video-based learning. Employing a modified probe-caught method, we recorded EEG data from participants engaged in viewing educational videos and subsequently focused on the discrimination between mind wandering (MW) and non-MW states. We systematically investigated various EEG complexity metrics, including metrics that reflect a system's regularity like multiscale permutation entropy (MPE), and metrics that reflect a system's dimensionality like detrended fluctuation analysis (DFA)...

Autism spectrum disorder is an increasingly prevalent and debilitating neurodevelopmental condition and an electroencephalogram (EEG) diagnostic challenge. Despite large amounts of electrophysiological research over many decades, an EEG biomarker for autism spectrum disorder (ASD) has not been found. We hypothesized that reductions in complex dynamical system behaviour in the human central nervous system as part of the macroscale neuronal function during cognitive processes might be detectable in whole EEG for higher-risk ASD adults...

Continuous adaptations of the movement system to changing environments or task demands rely on superposed fractal processes exhibiting power laws, that is, multifractality. The estimators of the multifractal spectrum potentially reflect the adaptive use of perception, cognition, and action. To observe time-specific behavior in multifractal dynamics, a multiscale multifractal analysis based on DFA (MFMS-DFA) has been recently proposed and applied to cardiovascular dynamics. Here we aimed at evaluating whether MFMS-DFA allows identifying multiscale structures in the dynamics of human movements...

MOTIVATION: The analysis of data obtained from continuous monitoring of respiratory signals (CMRS) holds significant importance in improving patient care, optimizing sports performance, and advancing scientific understanding in the field of respiratory health. RESULTS: The R package RespirAnalyzer provides an analytic tool specifically for feature extraction, fractal and complexity analysis for CMRS data. The package covers a wide and comprehensive range of data analysis methods including obtaining inter-breath intervals (IBI) series, plotting time series, obtaining summary statistics of IBI series, conducting power spectral density, multifractal detrended fluctuation analysis (MFDFA) and multiscale sample entropy analysis, fitting the MFDFA results with the extended binomial multifractal model, displaying results using various plots, etc...

Metabolic syndrome (MetS) has been linked to a higher prevalence of cardiac arrhythmias, the most frequent being atrial fibrillation, but the mechanisms are not well understood. One possible underlying mechanism may be an abnormal modulation of autonomic nervous system activity, which can be quantified by analysing heart rate variability (HRV). Our aim was to investigate the modifications of long-term HRV in an experimental model of diet-induced MetS to identify the early changes in HRV and the link between autonomic dysregulation and MetS components...

Heart rhythm complexity (HRC), a subtype of heart rate variability (HRV), is an important tool to investigate cardiovascular disease. In this study, we aimed to analyze serial changes in HRV and HRC metrics in patients with inferior ST-elevation myocardial infarction (STEMI) within 1 year postinfarct and explore the association between HRC and postinfarct left ventricular (LV) systolic impairment. We prospectively enrolled 33 inferior STEMI patients and 74 control subjects and analyzed traditional linear HRV and HRC metrics in both groups, including detrended fluctuation analysis (DFA) and multiscale entropy (MSE)...

The Chinese stock market exhibits many characteristics that deviate from the efficient market hypothesis and the trading volume contains a great deal of complexity information that the price cannot reflect. Do small or big orders drive trading volume? We studied the complex behavior of different orders from a microstructure perspective. We used ETF data of the CSI300, SSE50, and CSI500 indices and divided transactions into big and small orders. A multifractal detrended fluctuation analysis (MFDFA) method was used to study persistence...

A coarse-graining procedure, which involves averaging time series in non-overlapping windows followed by processing of the obtained multiple data sets, is the initial step in the multiscale entropy computation method. In this paper, we discuss how this procedure can be applied with other methods of time series analysis. Based on extended detrended fluctuation analysis (EDFA), we compare signal processing results for data sets with and without coarse-graining. Using the simulated data provided by the interacting nephrons model, we show how this procedure increases, up to 48%, the distinctions between local scaling exponents quantifying synchronous and asynchronous chaotic oscillations...

Complex systems in biology, climatology, medicine, and economy hold emergent properties such as non-linearity, adaptation, and self-organization. These emergent attributes can derive from large-scale relationships, connections, and interactive behavior despite not being apparent from their isolated components. It is possible to better comprehend complex systems by analyzing cross-correlations between time series. However, the accumulation of non-linear processes induces multiscale structures, therefore, a spectrum of power-law exponents (the fractal dimension) and distinct cyclical patterns...

BACKGROUND: Postural impairment is one of the most debilitating symptoms in people with Parkinson's disease (PD), which show faster and more variable oscillation during quiet stance than neurologically healthy individuals. Despite the center of pressure parameters can characterize PD's body sway, they are limited to uncover underlying mechanisms of postural stability and instability. RESEARCH QUESTION: Do a multiple domain analysis, including postural adaptability and rambling and trembling components, explain underlying postural stability and instability mechanisms in people with PD? METHOD: Twenty-four individuals (12 people with PD and 12 neurologically healthy peers) performed three 60-s trials of upright quiet standing on a force platform...

This study was based on the contemporary proposal that distinct states of consciousness are quantifiable by neural complexity and critical dynamics. To test this hypothesis, it was aimed at comparing the electrophysiological correlates of three meditation conditions using nonlinear techniques from the complexity and criticality framework as well as power spectral density. Thirty participants highly proficient in meditation were measured with 64-channel electroencephalography (EEG) during one session consisting of a task-free baseline resting (eyes closed and eyes open), a reading condition, and three meditation conditions (thoughtless emptiness, presence monitoring, and focused attention)...

The effectiveness of sensory substitution technology, such as haptic-based vibrotactile biofeedback (VBF), has been verified for balance training and rehabilitation. However, whether BF training changes postural dynamics in older people remains unknown. This study investigated the influence of VBF training on postural dynamics during single-leg standing in older adults, using detrended fluctuation analysis (DFA). Twenty older adults participated in this study. Measurement of postural sway comprised three phases: first measurement session as a baseline test, postural training (day 1), and second measurement session (day 2)...

The interest in photoplethysmography (PPG) for sleep monitoring is increasing because PPG may allow assessing heart rate variability (HRV), which is particularly important in breathing disorders. Thus, we aimed to evaluate how PPG wearable systems measure HRV during sleep at high altitudes, where hypobaric hypoxia induces respiratory disturbances. We considered PPG and electrocardiographic recordings in 21 volunteers sleeping at 4554 m a.s.l. (as a model of sleep breathing disorder), and five alpine guides sleeping at sea level, 6000 m and 6800 m a...

The Detrended Fluctuation Analysis (DFA) is a popular method for quantifying the self-similarity of the heart rate that may reveal complexity aspects in cardiovascular regulation. However, the self-similarity coefficients provided by DFA may be affected by an overestimation error associated with the shortest scales. Recently, the DFA has been extended to calculate the multifractal-multiscale self-similarity and some evidence suggests that overestimation errors may affect different multifractal orders. If this is the case, the error might alter substantially the multifractal-multiscale representation of the cardiovascular self-similarity...

BACKGROUND: Individuals with chronic obstructive pulmonary disease (COPD) commonly experience exacerbations, which may require hospital admission. Early detection of exacerbations, and therefore early treatment, could be crucial in preventing admission and improving outcomes. Our previous research has demonstrated that the pattern analysis of peripheral oxygen saturation (Sp O2 ) fluctuations provides novel insights into the engagement of the respiratory control system in response to physiological stress (hypoxia)...

Recent advancements in detrended fluctuation analysis (DFA) allow evaluating multifractal coefficients scale-by-scale, a promising approach for assessing the complexity of biomedical signals. The multifractality degree is typically quantified by the singularity spectrum width ( W SS ), a method that is critically unstable in multiscale applications. Thus, we aim to propose a robust multiscale index of multifractality, compare it with W SS and illustrate its performance on real biosignals. The proposed index is the cumulative function of squared increments between consecutive DFA coefficients at each scale n : α CF ( n )...

A comprehensive fault diagnosis method of rolling bearing about noise interference, fault feature extraction, and identification was proposed. Based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), detrended fluctuation analysis (DFA), and improved wavelet thresholding, a denoising method of CEEMDAN-DFA-improved wavelet threshold function was presented to reduce the distortion of the noised signal. Based on quantum-behaved particle swarm optimization (QPSO), multiscale permutation entropy (MPE), and support vector machine (SVM), the QPSO-MPE-SVM method was presented to construct the fault-features sets and realize fault identification...

Pulmonary hypertension (PH) is a fatal disease-even with state-of-the-art medical treatment. Non-invasive clinical tools for risk stratification are still lacking. The aim of this study was to investigate the clinical utility of heart rhythm complexity in risk stratification for PH patients. We prospectively enrolled 54 PH patients, including 20 high-risk patients (group A; defined as WHO functional class IV or class III with severely compromised hemodynamics), and 34 low-risk patients (group B). Both linear and non-linear heart rate variability (HRV) variables, including detrended fluctuation analysis (DFA) and multiscale entropy (MSE), were analyzed...

Recent research has clarified the existence of a networked system involving a cortical and subcortical circuitry regulating both cognition and cardiac autonomic control, which is dynamically organized as a function of cognitive demand. The main interactions span multiple temporal and spatial scales and are extensively governed by nonlinear processes. Hence, entropy and (multi)fractality in heart period time series are suitable to capture emergent behavior of the cognitive-autonomic network coordination. This study investigated how entropy and multifractal-multiscale analyses could depict specific cognitive-autonomic architectures reflected in the heart rate dynamics when students performed selective inhibition tasks...

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...