Developing Objective Motor Dysfunction Measures in Parkinson's Disease through Model Simulations

Parkinson's disease (PD) is a progressive neurological disorder primarily stemming from a reduction in dopamine levels in the basal ganglia. This reduced dopamine causes the emergence of motor symptoms such as tremor, bradykinesia, and muscular rigidity. Practitioners use subjective measures of motor dysfunction to monitor disease progression and evaluate treatment effectiveness. Development of objective measures of PD dysfunction could improve these procedures. This study applies a model of PD motor control to simulate reaching tasks that produce primarily open-loop movement and then use catch trials to engage feedback-driven movement. A key objective is to develop tasks that maximize the difference in observable parameters between healthy and PD reaching and characterize the level of PD dysfunction. This study analyzes simulations across a range of parameters to identify the measures that best meet this objective. This analysis will inform the design of future reaching tasks with patients interacting with a planar manipulandum to ultimately work towards improved diagnosis and monitoring of PD.