Relationship Between Clinical Measures of Upper Limb Movement Quality and Activity Poststroke
Mindy F Levin1, Vimonwan Hiengkaew2, Yongchai Nilanont3
11 McGill University and Centre for Interdisciplinary Research in Rehabilitation, Montreal, Quebec, Canada.
Abstract:
Background. Understanding the relationship between movement quality (impairment) and performance (activity) in poststroke patients is important for rehabilitation intervention studies. This has led to an interest in kinematic characterization of upper limb motor impairment. Since instrumented motion analysis is not readily clinically available, observational kinematics may be a viable alternative. Objective. To determine if upper limb movement quality during a reach-to-grasp task identified by observation could be used to describe the relationship between motor impairments and the time to perform functional tasks. Methods. Cross-sectional, secondary analysis of baseline data from 141 participants with stroke, age 18 to 85 years, who participated in a multicenter randomized controlled trial. Clinical assessment of movement quality using the Reaching Performance Scale for Stroke (RPSS-Close and Far targets) and of performance (activity) from the Wolf Motor Function Test (WMFT-7 items) was assessed. The degree to which RPSS component scores explained scores on WMFT items was determined by multivariable regression. Results. Clinically significant decreases (>2 seconds) in performance time for some of the more complex WMFT tasks involving prehension were predicted from RPSS-Close and Far target components. Trunk compensatory movements did not predict either increases or decreases in performance time for the WMFT tasks evaluated. Overall, the strength of the regression models was low. Conclusions. In lieu of kinematic analysis, observational clinical movement analysis may be a valid and accessible method to determine relationships between motor impairment, compensations and upper limb function in poststroke patients. Specific relationships are unlikely to generalize to all tasks due to kinematic redundancy and task specificity.
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