Dynamic Measures of Balance during Obstacle-Crossing in Self-Selected Gait in Individuals with Mild-to-Moderate Parkinson’s Disease
Source abstract
Abstract
Individuals with Parkinson’s disease (PD) have postural instability and gait dysfunction that lead to falls and disability with disease progression. Increased fall risk is particularly seen during challenging gait tasks such as obstacle-crossing. The purpose of this study was to determine if there were differences in dynamic postural control during self-paced walking and obstacle-crossing between persons with mild-to-moderate PD and healthy controls. Participants included nine individuals with PD and nine age- and gender-matched controls (CON). This study examined margin of stability metrics using instrumented 3D motion analysis during the two-step sequence of the obstacle-crossing task. Dynamic balance variables and spatiotemporal (ST) parameters at distinct gait events related to the leading (step one) and trailing leg (step two) were compared for the PD and CON groups using a mixed-model ANOVA. No differences were found between groups for ST gait parameters during obstacle-crossing, except for a significantly reduced step length (p = 0.005) for the trailing limb for the PD group. The PD group demonstrated significantly larger mean values for mediolateral center of pressure–center of mass (COP–COM) distance at first double support (p = 0.004) and center of pressure–extrapolated center of mass (COP–XCOM) distance at second double support (p = 0.016) for the second step. Our results suggest that the margin of stability may be useful in discerning postural control adaptations during obstacle negotiation in persons with PD.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Balance, Gait, and Falls Prevention · Cerebral Palsy and Movement Disorders · Parkinson's Disease Mechanisms and Treatments
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Physical Therapy & Athletic Training, Grand Valley State University, Grand Rapids, MI 49503, USA
Department of Mechanical Engineering, Penn State University, University Park, PA 16802, USA
Department of Statistics, Grand Valley State University, Allendale, MI 49401, USA
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