Year: 2025
Type: article
Study design: Observational Study
Abstract: The absence of sensitive tools for quantifying movement dysfunction hinders our ability to study the underlying causes of motor impairments and makes it difficult to demonstrate the effectiveness of therapeutic approaches. Consequently, it slows down progress in developing novel treatment protocols, including personalized impairment-targeted interventions. While there exist well-established metrics of static and quasi-static motion, such as reaching range, little emphasis has been placed on quantifying dynamic response-controlled and timing-sensitive movements where the continuous modulation of motor activity is required to respond to real-time stimuli. In this study, we employ robot-assisted virtual tasks that require dynamic motion in the upper limb, and develop metrics that assess dynamic capabilities by quantifying the frequency spectra of movement during these tasks. We assess chronic survivors of hemiparetic stroke across three dynamic tasks (n=13 for the first two tasks and n=48 for the third task). We find that hemiparetic stroke causes a significant decline in dynamic response at frequencies above 1.5Hz in the paretic upper limb, with the degree of functional loss dependent on the clinically assessed severity of motor impairment. Frequency-based metrics of dynamic motion could be used to assess performance during everyday activities, such as brushing teeth, cooking, or cleaning. A versatile quantitative assessment of dynamic motion can accelerate progress in understanding and rehabilitating functional dynamic motion in individuals with neuromotor disorders.
Institution: Northwestern University
Language: English
Subfield: Rehabilitation
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,990
Awards: G1161418017, Graduate Research Fellowship Program (GRFP), G292149420, Contralesional Corticobulbospinal Structural and Functional Changes Post Stroke: Biomarkers for the upper limb flexion synergy, CPS: Medium: Information based Control of Cyber-Physical Systems operating in uncertain environments
OpenAlex ID: W4414629547