Feasibility of home-based automated Parkinson's disease motor assessment

Abstract

Patients with Parkinson's disease (PD) receive therapies aimed at addressing a diverse range of motor symptoms. Motor complications in the form of symptom fluctuations and dyskinesias that commonly occur with chronic PD medication use may not be effectively captured by Unified Parkinson's Disease Rating Scale (UPDRS) assessments performed in the clinic. Therefore, home monitoring may be a viable adjunct tool to provide insight into PD motor symptom response to treatment. In this pilot study, we sought to evaluate the feasibility of capturing PD motor symptoms at home using a computer-based assessment system. Ten subjects diagnosed with idiopathic PD used the system at home and ten non-PD control subjects used the system in a laboratory. The Kinesia system consists of a wireless finger-worn motion sensor and a laptop computer with software for automated tremor and bradykinesia severity score assessments. Data from control subjects were used to develop compliance algorithms for rejecting motor tasks performed incorrectly. These algorithms were then applied to data collected from the PD subjects who used the Kinesia system at home to complete motor exams 3-6 times per day over 3-6 days. Motor tasks not rejected by the compliance algorithms were further processed for symptom severity. PD subjects successfully completed motor assessments at home, with approximately 97% of all motor task data files (1222/1260) accepted. These findings suggest that objective home monitoring of PD motor fluctuations is feasible.