NDLI: Adaptive Fractal Analysis Reveals Limits to Fractal Scaling in Center of Pressure Trajectories

Content Provider	Springer Nature Link
Author	Kuznetsov, Nikita Bonnette, Scott Gao, Jianbo Riley, Michael A.
Copyright Year	2012
Abstract	Fractal time series analysis methods are commonly used for analyzing center of pressure (COP) signals with the goal of revealing the underlying neuromuscular processes for upright stance control. The use of fractal methods is often coupled with the assumption that the COP is an instance of fractional Gaussian noise (fGn) or fractional Brownian motion (fBm). Our purpose was to evaluate the applicability of the fGn–fBm framework to the COP in light of several characteristics of COP signals revealed by a new method, adaptive fractal analysis (AFA). AFA quantifies how the variance of the residuals to fits of a globally smooth trend signal scales with the time scale at which the fits are performed. Application of AFA to COP signals revealed that there are potentially three fractal scaling regions in the COP as opposed to one as expected from a pure fGn or fBm process. The scaling region at the fastest scale was anti-persistent and spanned ~30–90 ms, the intermediate was persistent and spanned ~200 ms–1.9 s, and the slowest was anti-persistent and spanned ~5–40 s. The intermediate fractal scaling region was the most clearly defined, but it only contributed around 11% of the total spectral energy of the COP signal, indicating that other features of the COP signal contribute more importantly to the overall dynamics. Also, more than half of the Hurst exponents estimated for the intermediate region were greater than the theoretically expected range [0,1] for fGn–fBm processes. These results suggest the fGn–fBm framework is not appropriate for modeling COP signals. ON–OFF intermittency might provide a better modeling framework for the COP, and multiscale approaches may be more appropriate for analyzing COP data.
Starting Page	1646
Ending Page	1660
Page Count	15
File Format	PDF
ISSN	00906964
Journal	Annals of Biomedical Engineering
Volume Number	41
Issue Number	8
e-ISSN	15739686
Language	English
Publisher	Springer US
Publisher Date	2012-09-07
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Nonlinear analysis Detrended fluctuation analysis Adaptive fractal analysis Postural control Fractal scaling Center of pressure Biomedicine general Biomedical Engineering Biophysics and Biological Physics Mechanics Biochemistry
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering

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