Avoiding Virtual Obstacles During Treadmill Gait in Parkinson’s Disease

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Abstract

Falls often occur due to spontaneous loss of balance, but tripping over an obstacle during gait is also a frequent cause of falls (Sheldon, 1960; Stolze et al., 2004). Obstacle avoidance requires that appropriate modifications of the ongoing cyclical movement be initiated and completed in time. We evaluated the available response time to avoid a virtual obstacle in 26 Parkinson's disease (PD) patients (in the off-medication state) and 26 controls (18 elderly and 8 young), using a virtual obstacle avoidance task during visually cued treadmill walking. To maintain a stable baseline of stride length and visual attention, participants stepped on virtual “stepping stones” projected onto a treadmill belt. Treadmill speed and stepping stone spacing were matched to overground walking (speed and stride length) for each individual. Unpredictably, a stepping stone changed color, indicating that it was an obstacle. Participants were instructed to try to step short to avoid the obstacle. By using an obstacle that appeared at a precise instant, this task probed the time interval required for processing new information and implementing gait cycle modifications. Probability of successful avoidance of an obstacle was strongly associated with the time of obstacle appearance, with earlier-appearing obstacles being more easily avoided. Age was positively correlated (p < 0.001) with the time required to successfully avoid obstacles. Nonetheless, the PD group required significantly more time than controls (p = 0.001) to achieve equivalent obstacle-avoidance success rates after accounting for the effect of age. Slowing of gait adaptability could contribute to high fall risk in elderly and PD. Possible mechanisms may include disturbances in motor planning, movement execution, or disordered response inhibition.

Original languageEnglish (US)
Article number076
JournalFrontiers in Aging Neuroscience
StatePublished - 2019

Bibliographical note

Funding Information:
Emily Twedell, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States Michael McCabe, Trinity School of Medicine, Kingstown, Saint Vincent and the Grenadines

Funding Information:
This work was supported by the University of Minnesota Neuromodulation Innovations (MnDrive), the Udall Center grant of the National Institutes of Health Award Number P50NS098573, and the National Center for Advancing Translational Sciences of the National Institutes of Health Award Number UL1TR000114.

Publisher Copyright:
Copyright © 2019 Lu, Twedell, Elbasher, McCabe, MacKinnon and Cooper. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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