Motion Sensor Dyskinesia Assessment During Activities of Daily Living (P3.070)

OBJECTIVE: To determine the feasibility of using motion sensors to quantify dyskinesia in patients with Parkinson’s disease (PD) during activities of daily living. BACKGROUND: Dyskinesia throughout the levodopa dose cycle has been measured using a hand-worn motion sensor during the stationary tasks of arms resting and arms extended posture. Quantifying dyskinesia during unconstrained activities poses a unique challenge since these medication side effects are difficult to distinguish from voluntary movement. DESIGN/METHODS: Fifteen subjects with PD were instrumented with motion sensors units on each hand and heel. Data were recorded as subjects completed a series of simulated activities of daily living. Following recording in the OFF medication state, subjects were instructed to take their usual prescribed dose of medication. Recordings were repeated once per hour for three hours over the course of the dose cycle. Data recording sessions were videotaped for subsequent clinical scoring by two blinded movement disorder experts per the modified Abnormal Involuntary Movement Scale. The average of the upper extremity, lower extremity, and global dyskinesia severity scores across both raters was used as an overall measure for subsequent analyses. The kinematic data were processed into features and used in linear regression models, which output 0-4 dyskinesia severity scores. RESULTS: Movements when patients were in the ON medication state and experiencing dyskinesia were irregular with higher peak angular velocities, when compared to movements when patients were not experiencing dyskinesia. Dyskinesia scores predicted by the model were highly correlated with average clinician scores with a correlation coefficient of 0.86 and root-mean-square-error of 0.39. CONCLUSIONS: A system with two motion sensors units may provide an accurate measure of overall dyskinesia that can be used to monitor patients as they complete complex movements associated with typical activities. Such a system could provide valuable insight on symptom fluctuation in the context of daily life. Study Supported by: NIH/NINDS 7R43NS071882 Disclosure: Dr. Pulliam has received personal compensation for activities with Great Lakes NeuroTechnologies as an employee. Dr. Burack has received research support from Cleveland Medical Devices, Inc. Dr. Giuffrida has received personal compensation for activities with Great Lakes NeuroTechnologies Inc. as an employee. Dr. Giuffrida holds stock and/or stock options in Great Lakes NeuroTechnoliges Inc. which sponsored research in which Dr. Giuffrida was involved as an investigator. Dr. Mera has received personal compensation for activities with Great Lakes NeuroTechnologies Inc. as an employee.