Objective: To determine if poorer gait variability and gait coordination among mobility-limited older adults is related to their slower walking speed.
Design: Cross-sectional analysis.
Setting: University research laboratory.
Participants: Community-dwelling adults (N=69) 68 years or older with (Short Physical Performance Battery score ≤9; n=37) and without (n=32) mobility limitations.
Interventions: Not applicable.
Main Outcome Measures: The variability of step length, swing time percent, and step width. Gait coordination was assessed along with the Phase Coordination Index.
Results: The usual pace gait speed of those without mobility limitations was faster (1.22±0.14m/s vs 0.71±0.14m/s; P<.001) and less variable in all gait characteristics (all P<.001), with the exception of step width (P=.185), than those with limitations. When those without limitations slowed their walking pace (0.71m/s±0.14), their gait coordination became poorer (P<.001), and the variability of all gait characteristics increased (all P<.001) except for step width, which decreased (P=.002). When those without mobility limitations walked at a slow pace, they had better gait coordination (P=.008) and less variable step length (P=.014) and swing time percent (P=.036). The variability of stride time (P=.260) and step width (P=.385) were not significantly different than that of their peers with limitations.
Conclusions: Increased variability in some gait characteristics of mobility-limited older adults appears to be related to their slower walking speed. Gait coordination and the variability of step length and swing time percent may reflect intrinsic differences in mobility-limited older adults that are independent of walking speed.
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http://dx.doi.org/10.1016/j.apmr.2020.04.009 | DOI Listing |
Gait Posture
December 2024
Engineering Research Center of the Ministry of Education for Intelligent Rehabilitation Equipment and Detection Technologies, Hebei University of Technology, Tianjin 300401, PR China; Hebei Key Laboratory of Robot Sensing and Human-robot Interaction, Hebei University of Technology, Tianjin 300401, PR China; School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401, PR China. Electronic address:
Background: Gait feature recognition is crucial to improve the efficiency and coordination of exoskeleton assistance. The recognition methods based on surface electromyographic (sEMG) signals are popular. However, the recognition accuracy of these methods is poor due to ignoring the correlation of the time series of sEMG signals.
View Article and Find Full Text PDFJ Appl Biomech
January 2025
Rehabilitation Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Knee osteoarthritis (KOA) can have more pronounced effects on joint position sense (JPS) accuracy and gait characteristics. The aim of this study is to investigate the association between lower limb JPS and different aspects of gait pattern including gait asymmetry and variability and spatiotemporal coordination in individuals with bilateral KOA. In this cross-sectional study, lower limb JPS of 43 individuals with bilateral KOA (mild and moderate) were measured.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Rehabilitation Sciences, Ghent University, Ghent, Belgium.
Background: Increasing one's walking speed is an important goal in post-stroke gait rehabilitation. Insufficient arm swing in people post-stroke might limit their ability to propel the body forward and increase walking speed.
Purpose: To investigate the speed-dependent changes (and their contributing factors) in the arm swing of persons post-stroke.
PLoS One
January 2025
Department of Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia.
Top Stroke Rehabil
January 2025
Institut d'Investigació Biomèdica Sant Pau (IIB Sant Pau), Barcelona, Spain.
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