Much has been learned about the characteristics of gait in overground and treadmill walking. However, there are many contexts in which overground or treadmill walking might not be possible, such as in home-based physical therapy. In those cases, a surrogate task to index gait behavior would be a valuable tool. Thus, the purpose of this study was to evaluate the stride behavior characteristics of stationary stepping compared with treadmill walking. Healthy young adults (N = 10) preformed two 15-minute tasks: (1) treadmill walking and (2) stationary stepping. Several stride behavior characteristics were recorded, including the number of strides taken, minimum and maximum knee angle, stride interval mean, stride interval standard deviation, and detrended fluctuation analysis (DFA) alpha of the stride interval time series. The results showed that stride behavior was similar between tasks when examined at the group level. However, when individual level analyses were used to examine the reliability of each metric between tasks, poor reliability was observed in most metrics, indicating that stationary stepping may not be an appropriate surrogate task for overground or treadmill walking. These results are discussed in the context of a gait dynamics framework, with attention to task constraints that may have influenced the findings.
Christopher K. Rhea and Matthew W. Wittstein
Ruud J. R. Den Hartigh, Ralf F. A. Cox, Christophe Gernigon, Nico W. Van Yperen, and Paul L. C. Van Geert
The aim of this study was to examine (1) the temporal structures of variation in rowers’ (natural) ergometer strokes to make inferences about the underlying motor organization, and (2) the relation between these temporal structures and skill level. Four high-skilled and five lower-skilled rowers completed 550 strokes on a rowing ergometer. Detrended Fluctuation Analysis was used to quantify the temporal structure of the intervals between force peaks. Results showed that the temporal structure differed from random, and revealed prominent patterns of pink noise for each rower. Furthermore, the high-skilled rowers demonstrated more pink noise than the lower-skilled rowers. The presence of pink noise suggests that rowing performance emerges from the coordination among interacting component processes across multiple time scales. The difference in noise pattern between high-skilled and lower-skilled athletes indicates that the complexity of athletes’ motor organization is a potential key characteristic of elite performance.
Nicholas S. Ryan, Paul A. Bruno, and John M. Barden
) of the parameter of interest over a series of consecutive strides. 1 The pattern (or temporal structure) of the variability can be quantified by using detrended fluctuation analysis to calculate a fractal scaling exponent ( α ) that evaluates the degree to which long-range, self
Takuya Ibara, Makoto Takahashi, Koichi Shinkoda, Mahito Kawashima, and Masaya Anan
) = ∑ i = 1 m ( x i − x ¯ ) . (3) Here, x i and x ¯ indicate the original time series data and the mean value of the time series data, respectively. Figure 2 —The detrended fluctuation analysis protocol for estimating the scaling exponent α. (a) The acceleration time series data in the medial
Scott W. Ducharme and Richard E.A. van Emmerik
indicates the signal at any given point exhibits dependence upon previous and future states. Figure 5 —Illustration of detrended fluctuation analysis (DFA) method on a biophysical signal (here, stride interval). The signal is sectioned into nonoverlapping windows of varying sizes; here illustrated as 10
Philip W. Fink, Sarah P. Shultz, Eva D’Hondt, Matthieu Lenoir, and Andrew P. Hills
must be relied upon (e.g., when other sources of perceptual information such as vision are removed), multifractal behavior may be more readily observed. Here, a multifractal detrended fluctuation analysis (MFDFA; Ihlen, 2012 ; Kantelhardt et al., 2002 ; see Kelty-Stephen, Palatinus, Saltzman
Stephen M. Glass, Brian L. Cone, Christopher K. Rhea, Donna M. Duffy, and Scott E. Ross
each channel. The nonlinear outcomes used in this study were (1) detrended fluctuation analysis (DFA) and (2) multivariate multiscale sample entropy (MMSE). These 2 outcomes were selected as indicators of long-range correlation and multiscale complexity, respectively. 22 Both nonlinear outcomes were
Denine Ellis, Ervin Sejdic, Karl Zabjek, and Tom Chau
The strength of time-dependent correlations known as stride interval (SI) dynamics has been proposed as an indicator of neurologically healthy gait. Most recently, it has been hypothesized that these dynamics may be necessary for gait efficiency although the supporting evidence to date is scant. The current study examines over-ground SI dynamics, and their relationship with the cost of walking and physical activity levels in neurologically healthy children aged nine to 15 years. Twenty participants completed a single experimental session consisting of three phases: 10 min resting, 15 min walking and 10 min recovery. The scaling exponent (α) was used to characterize SI dynamics while net energy cost was measured using a portable metabolic cart, and physical activity levels were determined based on a 7-day recall questionnaire. No significant linear relationships were found between a and the net energy cost measures (r < .07; p > .25) or between α and physical activity levels (r = .01, p = .62). However, there was a marked reduction in the variance of α as activity levels increased. Over-ground stride dynamics do not appear to directly reflect energy conservation of gait in neurologically healthy youth. However, the reduction in the variance of α with increasing physical activity suggests a potential exercise-moderated convergence toward a level of stride interval persistence for able-bodied youth reported in the literature. This latter finding warrants further investigation.
Jeff A. Nessler, Tomas Gonzales, Eric Rhoden, Matthew Steinbrick, and Charles J. De Leone
The purpose of this study was to examine the effects of interpersonal synchronization of stepping on stride interval dynamics during over-ground walking. Twenty-seven footswitch instrumented subjects walked under three conditions: independent (SOLO), alongside a partner (PAIRED), and side by side with intentional synchronization (FORCED). A subset of subjects also synchronized stepping to a metronome (MET). Stride time power spectral density and detrended fluctuation analysis revealed that the rate of autocorrelation decay in stride time was similar for both the SOLO and PAIRED conditions, but was significantly reduced during the FORCED and MET conditions (p=0.03 & 0.002). Stride time variability was also significantly increased for the FORCED and MET conditions (p<0.001). These data suggest that forced synchronization of stepping results in altered stride interval dynamics, likely through increased active control by the CNS. Passive side by side stepping, where synchronization is subconscious, does not appreciably alter stepping in this manner.
Jeffrey P. Kaipust, Jessie M. Huisinga, Mary Filipi, and Nicholas Stergiou
The purpose of this study was to determine the differences in gait variability between patients with multiple sclerosis (MS) and healthy controls during walking at a self-selected pace. Methods: Kinematics were collected during three minutes of treadmill walking for 10 patients with MS and 10 healthy controls. The Coefficient of Variation (CoV), the Approximate Entropy (ApEn) and the Detrended Fluctuation Analysis (DFA) were used to investigate the fluctuations present in stride length and step width from continuous strides. Results: ApEn revealed that patients with MS had significantly lower values than healthy controls for stride length (p < .001) and step width (p < .001). Conclusions: ApEn results revealed that the natural fluctuations present during gait in the stride length and step width time series are more regular and repeatable in patients with MS. These changes implied that patients with MS may exhibit reduced capacity to adapt and respond to perturbations during gait.