Step-to-Step Variability in Treadmill Walking: Influence of Rhythmic Auditory Cueing

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Abstract

While walking, human beings continuously adjust step length (SpL), step time (SpT), step speed (SpS = SpL/SpT) and step width (SpW) by integrating both feedforward and feedback mechanisms. These motor control processes result in correlations of gait parameters between consecutive strides (statistical persistence). Constraining gait with a speed cue (treadmill) and/or a rhythmic auditory cue (metronome), modifies the statistical persistence to anti-persistence. The objective was to analyze whether the combined effect of treadmill and rhythmic auditory cueing (RAC) modified not only statistical persistence, but also fluctuation magnitude (standard deviation, SD), and stationarity of SpL, SpT, SpS and SpW. Twenty healthy subjects performed 6×5 min. walking tests at various imposed speeds on a treadmill instrumented with foot-pressure sensors. Freely-chosen walking cadences were assessed during the first three trials, and then imposed accordingly in the last trials with a metronome. Fluctuation magnitude (SD) of SpT, SpL, SpS and SpW was assessed, as well as NonStationarity Index (NSI), which estimates the dispersion of local means in the times series (SD of 20 local means over 10 steps). No effect of RAC on fluctuation magnitude (SD) was observed. SpW was not modified by RAC, what is likely the evidence that lateral foot placement is separately regulated. Stationarity (NSI) was modified by RAC in the same manner as persistent pattern: Treadmill induced low NSI in the time series of SpS, and high NSI in SpT and SpL. On the contrary, SpT, SpL and SpS exhibited low NSI under RAC condition. We used relatively short sample of consecutive strides (100) as compared to the usual number of strides required to analyze fluctuation dynamics (200 to 1000 strides). Therefore, the responsiveness of stationarity measure (NSI) to cued walking opens the perspective to perform short walking tests that would be adapted to patients with a reduced gait perimeter.

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Effect size, confidence interval and statistical significance: a practical guide for biologists.

Shinichi Nakagawa, Innes C Cuthill (2007)

Null hypothesis significance testing (NHST) is the dominant statistical approach in biology, although it has many, frequently unappreciated, problems. Most importantly, NHST does not provide us with two crucial pieces of information: (1) the magnitude of an effect of interest, and (2) the precision of the estimate of the magnitude of that effect. All biologists should be ultimately interested in biological importance, which may be assessed using the magnitude of an effect, but not its statistical significance. Therefore, we advocate presentation of measures of the magnitude of effects (i.e. effect size statistics) and their confidence intervals (CIs) in all biological journals. Combined use of an effect size and its CIs enables one to assess the relationships within data more effectively than the use of p values, regardless of statistical significance. In addition, routine presentation of effect sizes will encourage researchers to view their results in the context of previous research and facilitate the incorporation of results into future meta-analysis, which has been increasingly used as the standard method of quantitative review in biology. In this article, we extensively discuss two dimensionless (and thus standardised) classes of effect size statistics: d statistics (standardised mean difference) and r statistics (correlation coefficient), because these can be calculated from almost all study designs and also because their calculations are essential for meta-analysis. However, our focus on these standardised effect size statistics does not mean unstandardised effect size statistics (e.g. mean difference and regression coefficient) are less important. We provide potential solutions for four main technical problems researchers may encounter when calculating effect size and CIs: (1) when covariates exist, (2) when bias in estimating effect size is possible, (3) when data have non-normal error structure and/or variances, and (4) when data are non-independent. Although interpretations of effect sizes are often difficult, we provide some pointers to help researchers. This paper serves both as a beginner's instruction manual and a stimulus for changing statistical practice for the better in the biological sciences.

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Active control of lateral balance in human walking.

Arthur Kuo, C Bauby (2000)

We measured variability of foot placement during gait to test whether lateral balance must be actively controlled against dynamic instability. The hypothesis was developed using a simple dynamical model that can walk down a slight incline with a periodic gait resembling that of humans. This gait is entirely passive except that it requires active control for a single unstable mode, confined mainly to lateral motion. An especially efficient means of controlling this instability is to adjust lateral foot placement. We hypothesized that similar active feedback control is performed by humans, with fore-aft dynamics stabilized either passively or by very low-level control. The model predicts that uncertainty within the active feedback loop should result in variability in foot placement that is larger laterally than fore-aft. In addition, loss of sensory information such as by closing the eyes should result in larger increases in lateral variability. The control model also predicts a slight coupling between step width and length. We tested 15 young normal human subjects and found that lateral variability was 79% larger than fore-aft variability with eyes open, and a larger increase in lateral variability (53% vs. 21%) with eyes closed, consistent with the model's predictions. We also found that the coupling between lateral and fore-aft foot placements was consistent with a value of 0.13 predicted by the control model. Our results imply that humans may harness passive dynamic properties of the limbs in the sagittal plane, but must provide significant active control in order to stabilize lateral motion.

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Mechanical and metabolic determinants of the preferred step width in human walking.

Alice A. Kuo, Rodger Kram, J Donelan (2001)

We studied the selection of preferred step width in human walking by measuring mechanical and metabolic costs as a function of experimentally manipulated step width (0.00-0.45L, as a fraction of leg length L). We estimated mechanical costs from individual limb external mechanical work and metabolic costs using open circuit respirometry. The mechanical and metabolic costs both increased substantially (54 and 45%, respectively) for widths greater than the preferred value (0.15-0.45L) and with step width squared (R(2) = 0.91 and 0.83, respectively). As predicted by a three-dimensional model of walking mechanics, the increases in these costs appear to be a result of the mechanical work required for redirecting the centre of mass velocity during the transition between single stance phases (step-to-step transition costs). The metabolic cost for steps narrower than preferred (0.10-0.00L) increased by 8%, which was probably as a result of the added cost of moving the swing leg laterally in order to avoid the stance leg (lateral limb swing cost). Trade-offs between the step-to-step transition and lateral limb swing costs resulted in a minimum metabolic cost at a step width of 0.12L, which is not significantly different from foot width (0.11L) or the preferred step width (0.13L). Humans appear to prefer a step width that minimizes metabolic cost.

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Author and article information

Contributors

Adrian LR. Thomas: Role: Editor

Journal

Journal ID (nlm-ta): PLoS One

Journal ID (iso-abbrev): PLoS ONE

Journal ID (publisher-id): plos

Journal ID (pmc): plosone

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, USA )

ISSN (Electronic): 1932-6203

Publication date Collection: 2012

Publication date (Electronic): 8 October 2012

Volume: 7

Issue: 10

Electronic Location Identifier: e47171

Affiliations

[1 ]IRR, Institut de Recherche en Réadaptation, Sion, Switzerland

[2 ]Clinique romande de réadaptation SuvaCare, Sion, Switzerland

University of Oxford, United Kingdom

Author notes

* E-mail: philippe.terrier@ 123456crr-suva.ch

Competing Interests: The author has declared that no competing interests exist.

Conceived and designed the experiments: PT. Performed the experiments: PT. Analyzed the data: PT. Contributed reagents/materials/analysis tools: PT. Wrote the paper: PT.

Article

Publisher ID: PONE-D-12-24159

DOI: 10.1371/journal.pone.0047171

PMC ID: 3466237

PubMed ID: 23056604

SO-VID: 700e030e-3325-4a37-b0bd-48b172ada4ac

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Date received : 13 August 2012

Date accepted : 10 September 2012

Page count

Pages: 9

Funding

The study was supported by the Swiss accident insurance company SUVA, which is an independent, non-profit company under public law. The IRR (Institute for Research in Rehabilitation) is supported by the State of Valais and the City of Sion. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Step-to-Step Variability in Treadmill Walking: Influence of Rhythmic Auditory Cueing

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Abstract

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Most cited references 31

Effect size, confidence interval and statistical significance: a practical guide for biologists.

Active control of lateral balance in human walking.

Mechanical and metabolic determinants of the preferred step width in human walking.

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