Effect of treadmill walking on the stride interval dynamics of human gait

doi:10.1016/j.gaitpost.2009.06.017

Gait & Posture

Volume 30, Issue 4, November 2009, Pages 431-435

https://doi.org/10.1016/j.gaitpost.2009.06.017 Get rights and content

Abstract

Metronomic walking has been found to diminish the statistical persistence intrinsic to the stride interval time series of human gait. Since treadmill walking (TW) possesses a similar form of external pacing, we proposed to study the disruptions in the natural neuromuscular rhythms of gait during TW. Treadmill walking is a widespread rehabilitative tool, however, its effect on an individual’s stride dynamics is not well understood. To better elucidate potential effects, we tested the hypothesis that TW without handrails would diminish the statistical persistence in an individual’s stride interval time series. The scaling exponent $(α)$ was employed in this study as a measure of the statistical persistence of the stride interval time series. Sixteen able-bodied young adults (mean age: $23.3 \pm 3.3$ years) were instructed to walk at a self-selected comfortable pace for 15 min in three different conditions in a randomized order: (1) overground walking, (2) TW without holding a handrail (NoRail) and (3) TW while holding a front handrail (Rail). The $α$ did not differ significantly between the overground and NoRail conditions ( $P > 0.5$ ). However, the $α$ of the Rail condition $(α = 0.92 \pm 0.10)$ differed significantly from both the overground ( $α = 0.83 \pm 0.06$ ; $P < 0.015$ ) and NoRail conditions ( $α = 0.82 \pm 0.08$ ; $P < 0.01$ ). In contrast, stride interval variability did not change between walking conditions $(P > 0.5)$ . These findings indicate that comfortable-paced TW does not diminish the intrinsic stride dynamics of human gait.

Introduction

The stride interval (SI), defined as the time between consecutive heel strikes of the same foot, was thought to fluctuate randomly during natural bipedal ambulation until the last decade. Hausdorff et al. showed that SIs actually fluctuate in a complex manner [1]. They implied via detrended fluctuation analysis (DFA) that natural overground walking exhibits long-range correlations, i.e., fluctuations in SIs are correlated to fluctuations up to hundreds of strides earlier [1], [2]. However, DFA cannot always infer the existence of long-range correlations [3], [4]. In light of this, processes yielding a slope ( $α$ ) for the fluctuation function in a log–log representation greater than 0.5 will herein instead be referred to as statistically persistent.

The statistical persistence of an individual’s gait is commonly measured by $α$ , also known as a scaling exponent, derived from a DFA of an individual’s SI time series. The able-bodied individual typically exhibits an $α$ value ranging from 0.8 to 1.0, whereas advanced aging and individuals with Parkinson’s disease and Huntington’s disease typically present with significantly lower values closer to 0.5 [2], [5], [6]. This decline in $α$ reflects a more random time series with weakened statistical persistence. Subsequently, it was found that individuals exhibiting lower $α$ values were more prone to falling [7]. West and Griffin further hypothesized that $α$ may be a potential indicator of an individual’s ability to adapt to changing environmental conditions during walking [8], [9].

Interestingly, it was also found that metronomic walking (MW), i.e., walking to the beat of a metronome, resulted in lower $α$ values in able-bodied individuals [2]. This disturbance in the natural neuromuscular rhythms of human gait may negatively impact an individual’s ability to adapt to dynamical situations in the surrounding environment and increase the risk of falling [7], [8], [9]. In rehabilitation, treadmills are often employed in therapeutic interventions. During treadmill walking (TW) the individual is entrained to an external pace akin to MW. Therefore, we hypothesized that TW would also disturb the natural SI dynamics in human subjects. Previously, Frenkel-Toledo et al. also found that the $α$ was reduced during TW while holding handrails as compared to overground walking with a walker [10]. Various other studies have investigated the SI dynamics of gait [2], [5], [6], [7], [11], [12], however they did not specifically compare the SI dynamics between overground and treadmill walking with or without holding handrails. Considering the importance and widespread application of treadmills in rehabilitation, it is of critical value to study the effect of TW with and without the use of handrails on SI dynamics.

The objective of this study was twofold: (1) to investigate the impact of TW without using a handrail on stride interval dynamics as compared to overground walking and (2) to examine the effect of employing a handrail during TW on stride interval dynamics.

Section snippets

Participants

Sixteen able-bodied participants (six males) were recruited from the Bloorview Research Institute at the Toronto Bloorview Kids Rehab Centre as a convenience sample. Participants had normal or corrected-to-normal vision and were all right-foot dominant. Participants were excluded if they had any previous or existing neurological pathology, injury or illness likely to affect their gait. Mean age was $23.3 \pm 3.3$ (SD) years. Mean height and mass were $1.68 \pm 0.08$ (SD) m and $59.9 \pm 11.5$ (SD) kg,

Results

Examples of the stride interval time series during each of the three walking conditions and the corresponding fluctuation analyses are shown in Fig. 1(a) and (b), respectively. The scaling exponent of the overground and NoRail conditions were not significantly different ( $P > 0.5$ ). However, the $α$ of the Rail condition $(α = 0.92 \pm 0.10)$ was significantly greater than the $α$ from both the overground ( $α = 0.83 \pm 0.06$ ; $P < 0.015$ ) and NoRail ( $α = 0.82 \pm 0.08$ ; $P < 0.01$ ) conditions as shown in Table 1. However, stride

Discussion

In this gait study investigating the effects of treadmill walking on the stride interval dynamics in able-bodied participants, we found three key results: (1) the scaling exponent ( $α$ ) was not significantly different between the overground and NoRail conditions; (2) the Rail condition displayed a significantly increased $α$ compared to the overground and NoRail conditions; and (3) stride interval variability and gait speed were not associated with $α$ .

Conclusion

In this study, the stride dynamics of overground walking, treadmill walking without holding a handrail and treadmill walking while holding a handrail were compared and a possible physiological explanation was discussed. It was found that treadmill walking at a self-selected comfortable pace did not diminish the intrinsic stride dynamics as compared to natural overground gait. Thus, treadmill walking does not seem to pose a risk to an individual’s natural stride dynamics, which is a potential

Conflict of interest statement

There are no conflicts of interest between the co-authors of the paper.

Acknowledgements

We thank all the participants for their participation, time and effort. We also thank Ka Lun Tam for his technical support and Ervin Sejdic for his invaluable input on nonlinear analyses and proofreading. This work was supported in part by the Bloorview Children’s Hospital Foundation.

Study sponsors had no involvement in the study design, in the collection, analysis and interpretation of data, in the writing of the manuscript or in the decision to submit the manuscript for publication.

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AFA and DFA do not produce equivalent estimates of the fractal exponent α in stride time dynamics. Estimates of the fractal exponent α obtained with AFA or DFA algorithms therefore should not be used interchangeably. Standard errors were lower when derived with AFA. Fractal exponents calculated with AFA may be more sensitive to conditions that influence stride time fractal dynamics than are measures calculated with DFA.
Adaptive treadmill walking encourages persistent propulsion
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How do spatiotemporal and propulsive gait variables vary from stride to stride during adaptive treadmill walking, and how do they compare to fixed-speed treadmill walking?
Eighteen young healthy subjects walked on an instrumented split-belt treadmill in the adaptive and fixed-speed modes for 10 minutes at their comfortable speed. Kinetic data was collected from the treadmill. Detrended fluctuation analysis was applied to the time series data. Shapiro-Wilk tests assessed normality and one-way repeated measures ANOVAs compared between adaptive, fixed-speed, and randomly shuffled conditions at a Bonferroni-corrected significance level of 0.0055.
Stride time, stride length, step length, and braking impulse were persistent (α > 0.5) in the adaptive and fixed-speed conditions. Adaptive and fixed-speed were different from each other. Stride speed was persistent in the adaptive condition and anti-persistent (α < 0.5) in the fixed-speed condition. Peak propulsive force, peak braking force, and propulsive impulse were persistent in the adaptive condition but not the fixed-speed condition (α ≈ 0.5). Net impulse was non-persistent in the adaptive and fixed-speed conditions. All variables were non-persistent in the shuffled condition.
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Citation Excerpt :
However, they neglected coordination between the gait and upper trunk. Although there was a significant difference in the mean stride interval, the intrinsic stride dynamics did not diminish during TW [34], which means that natural stride dynamics, which are a potential indicator of falling or a person’s ability to adapt to changing environmental conditions during walking, are not at-risk during TW. Therefore, TW is still a suitable rehabilitation tool.
The equivalency of treadmill and overground walking has been investigated in a large number of studies. However, no systematic review has been performed on this topic.
The aim of this study was to compare the biomechanical, electromyographical and energy consumption outcomes of motorized treadmill and overground walking.
Five databases, ScienceDirect, SpringerLink, Web of Science, PubMed, and Scopus, were searched until January 13, 2021. Studies written in English comparing lower limb biomechanics, electromyography and energy consumption during treadmill and overground walking in healthy young adults (20–40 years) were included.
Twenty-two studies (n = 409 participants) were included and evaluated via the Cochrane Collaboration’s tool. These 22 studies showed that some kinematic (reduced pelvic ROM, maximum hip flexion angle for females, maximum knee flexion angle for males and cautious gait pattern), kinetic (sagittal plane joint moments: dorsiflexor moments, knee extensor moments and hip extensor moments and sagittal plane joint powers at the knee and hip joints, peak backwards, lateral and medial COP velocities and propulsive forces during late stance) and electromyographic (lower limbs muscles activities) outcome measures were significantly different for motorized treadmill and overground walking.
Spatiotemporal, kinematic, kinetic, electromyographic and energy consumption outcome measures were largely comparable for motorized treadmill and overground walking. However, the differences in kinematic, kinetic and electromyographic parameters should be taken into consideration by clinicians, trainers, and researchers when working on new protocols related to patient rehabilitation, fitness rooms or research as to be as close as possible to the outcome measures of overground walking. The protocol registration number is CRD42021236335 (PROSPERO International Prospective Register of Systematic Reviews).
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^☆: Source: Bloorview Children’s Hospital Foundation, University of Toronto Fellowship, Canada Research Chairs Program.

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Effect of treadmill walking on the stride interval dynamics of human gait☆

Abstract

Introduction

Section snippets

Participants

Results

Discussion

Conclusion

Conflict of interest statement

Acknowledgements

Gait Posture

Chaos Sol Fract

Gait Posture

Hum Mov Sci

Arch Phys Med Rehabil

Gait Posture

Neuroimage

Brain Res Bull

Gait Posture

Gait Posture

Electroencephalogr Clin Neurophysiol

Gait Posture

Is walking a random walk? Evidence for long-range correlations in stride interval of human gait

J Appl Physiol

Fractal dynamics of human gait: stability of long-range correlations in stride interval fluctuations

J Appl Physiol

Tempting long-memory—on the interpretation of DFA results

Nonlinear Proc Geophys

Estimation and interpretation of 1/falpha noise in human cognition

Psychon Bull Rev

Altered fractal dynamics of gait: reduced stride-interval correlations with aging and Huntington’s disease

J Appl Physiol

Dynamic markers of altered gait rhythm in amyotrophic lateral sclerosis

J Appl Physiol