Article

Detrended fluctuation analyses (DFA) have been widely used to quantify
stride-to-stride temporal correlations in human walking. However, significant
questions remain about how to properly interpret these statistical properties
physiologically. Here, we propose a simpler and more parsimonious interpretation
than previously suggested. Seventeen young healthy adults walked on a motorized
treadmill at each of 5 speeds. Time series of consecutive stride lengths (SL) and
stride times (ST) were recorded. Time series of stride speeds were computed as
SS=SL/ST. SL and ST exhibited strong statistical persistence (alpha>>0.5).
However, SS consistently exhibited slightly anti-persistent (alpha<0.5) dynamics.
We created three surrogate data sets to directly test specific hypotheses about
possible control processes that might have generated these time series. Subjects
did not choose consecutive SL and ST according to either independently
uncorrelated or statistically independent auto-regressive moving-average (ARMA)
processes. However, cross-correlated surrogates, which preserved both the
auto-correlation and cross-correlation properties of the original SL and ST time
series successfully replicated the means, standard deviations, and (within
computational limits) DFA alpha exponents of all relevant gait variables. These
results suggested that subjects controlled their movements according to a
two-dimensional ARMA process that specifically sought to minimize
stride-to-stride variations in walking speed (SS). This interpretation fully
agrees with experimental findings and also with the basic definitions of
statistical persistence and anti-persistence. Our findings emphasize the
necessity of interpreting DFA alpha exponents within the context of the control
processes involved and the inherent biomechanical and neuro-motor redundancies
available.
CI - Copyright (c) 2010 Elsevier B.V. All rights reserved.

Langue : ANGLAIS