Fractal Analysis of Human Gait Variability via Stride Interval Time Series

Abstract

Fractal analysis of stride interval time series is a useful tool in human gait research which could be used as a marker for gait adaptability, gait disorder, and fall risk among patients with movement disorders. This study is designed to systematically and comprehensively investigate two practical aspects of fractal analysis which significantly affect the outcome: the series length and the parameters used in the algorithm. The Hurst exponent, scaling exponent, and/or fractal dimension are computed from both simulated and experimental data using three fractal methods, namely detrended fluctuation analysis, box-counting dimension, and Higuchi's fractal dimension. The advantages and drawbacks of each method are discussed, in terms of biases and variability. The results demonstrate that a careful selection of fractal analysis methods and their parameters is required, which is dependent on the aim of study (either analyzing differences between experimental groups or estimating an accurate determination of fractal features). A set of guidelines for the selection of the fractal methods and the length of stride interval time series is provided, along with the optimal parameters for a robust implementation for each method.

Stochastic Resonance Reduces Sway and Gait Variability in Individuals With Unilateral Transtibial Amputation: A Pilot Study

“…The current paper relied on linear measures (e.g., means and standard deviations) to make inferences about the effects of stochastic resonance on the control and stability of gait and posture. However, a large literature suggests that, in addition to linear outcome measures, it is critical to examine the temporal (e.g., fractal) properties these behaviors exhibit (Hausdorff et al, 1995;Hausdorff, 2005;West and Latka, 2005;Xue et al, 2016;Phinyomark et al, 2020) that often covary with cases of aging and neurodegenerative disease (Hausdorff, 2007(Hausdorff, , 2009). While we did not investigate these properties in the present study, we might expect to see similar trends in individuals with lower limb amputation.…”

Age-Related Changes in Standing Balance in Preschoolers Using Traditional and Nonlinear Methods

“…The variability of COP sway decreased for the 5-year-old children compared with 3- and 4-year-old children, as shown with higher DFA 1 _ap, consistent with the previous study ( Lobo Da Costa et al, 2019 ). Three- and four-year-old children present a more complicated COP sway than 5-year-old children ( Lobo Da Costa et al, 2019 ; Phinyomark et al, 2020 ). The higher DFA values are linked to a better standing balance performance ( van den Hoorn et al, 2018 ).…”

Immersive Virtual Reality to Restore Natural Long-Range Autocorrelations in Parkinson’s Disease Patients’ Gait During Treadmill Walking

“…Temporal organization of stride duration variability was assessed by LRA computation using the evenly spaced averaged version of the detrended fluctuation analysis (DFA) ( Almurad and Delignières, 2016 ) to obtain α exponent. This method was chosen given its robustness regarding stationary and non-stationary processes ( Phinyomark et al, 2020 ; Ravi et al, 2020 ). LRA are present when α exponent values are between 0.5 and 1 meaning that large stride duration fluctuations tend to be followed by other large fluctuations, and vice-versa.…”