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Updated: Dec 11, 2025

Influence of Step-Width Manipulation on Running Biomechanics
Published on: February 28, 2025
Treadmill-belt width, but not feedback from the lower visual field, influences the noise characteristics of step
David M Desmet1, Aaron D Westbrook1, Mark D Grabiner1
1Department of Kinesiology and Nutrition, University of Illinois at Chicago, Chicago, IL 60612, United States.
Abstract:
Step kinematic variability, which has been associated with gait-related fall risk, is thought to be attributed to neuromotor noise. Altered neuromotor control of step kinematics would be expected to manifest as changes in the noise-related characteristics of the step kinematic time series. This study determined the effects of eliminating feedback from the lower visual field and reducing treadmill-belt width on the noise characteristics of step width time series and statistical measures of step width variability during treadmill walking. We hypothesized that eliminating feedback from the lower visual field and reducing treadmill-belt width would both alter the noise characteristics of step width time series, reflected by decreased fractal scaling, and increase statistical measures of step width variability. Eighteen young adults performed four randomly ordered walking trials during which we manipulated visual feedback from the lower visual field (normal and obstructed) and treadmill-belt width (wide and narrow). Reducing treadmill-belt width, but not eliminating feedback from the lower visual field, significantly reduced the fractal scaling of step width time series, indicating a shift towards white, uncorrelated noise. These results suggest that accounting for the influence of treadmill-belt width on step width time series may be an important consideration in both laboratory and clinical settings. Further work is needed to clarify the effects of vision on measures of step width, identify the mechanism(s) underlying the observed shift towards white, uncorrelated noise associated with reduced treadmill-belt width, and to assess the potential relationship between the noise characteristics of step width time series and fall risk.
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