Automated Assessment of Motor Impairments in Parkinson's Disease

A system for the automatic assessment of motor impairments in Parkinson's Disease (PD) is presented. The interface, built around optical RGB-Depth devices, allows for tracking of hands and body movements during the performance of standard upper and lower limb tasks, as specified by the Unified Parkinson's Disease Rating Scale (UPDRS). The assessment of the different tasks is performed by machine learning techniques. Selected kinematic parameters characterizing the movements are input to trained classifiers to rate the motor performance. The accurate tracking and characterization of the movements allows for an automatic and objective assessment of the UPDRS tasks, making feasible the monitoring of motor fluctuations also at-home for telemedicine or neurorehabilitation purposes.