Optimizing deep brain stimulation settings using wearable sensing technology

Abstract

Parkinson's disease is a neurodegenerative movement disorder resulting in rigidity, bradykinesia (slowness), tremor and gait disorder. Deep brain stimulation (DBS) of the subthalamic nucleus has been shown to be effective in managing symptoms, but quantitative methods to facilitate the adjustment of the stimulator settings are needed. In this paper, we present preliminary results from a study aimed at investigating the use of wearable sensors to quantitatively track changes in the severity of symptoms in patients with Parkinson's disease undergoing programming of the stimulator. We developed a technique that relies upon features derived from wearable sensors to track changes in the severity of symptoms over a period during which patient's motor activities are monitored. Preliminary results indicate that wearable sensors could be utilized to help clinicians achieve optimal settings of the stimulator by providing quantitative feedback concerning the impact of different settings on the severity of Parkinsonian symptoms.