Closed-Loop Deep Brain Stimulation in Parkinson’s Disease with Distributed, Proportional plus Integral Control

Abstract

<p>Continuous deep brain stimulation (cDBS) of either subthalamic nucleus (STN) or globus pallidus (GP) is an effective therapy in Parkinson’s Disease (PD) but is inherently limited by lack of responsiveness to dynamic, fluctuating symptoms intrinsic to the disease. Adaptive DBS (aDBS) adjusts stimulation in response to neural biomarkers to improve both efficacy and battery life. This thesis discusses 1) the development of dual target STN+GP aDBS with a novel, external adaptive controller and 2) the outcomes from a first in-human clinical trial in PD patients (n = 6; NCT #03815656) in order to assess efficacy of the aDBS controller.We performed random amplitude experiments to probe system dynamics and thus estimated initial aDBS parameters. We then implemented an innovative proportional plus integral (PI) aDBS using a novel distributed architecture. The PI aDBS controller was first evaluated in the clinic settings and then compared to cDBS in the home settings. The results showed that the PI aDBS control reduced average power delivered while preserving improved Unified Parkinson’s Disease Rating Scale (UPDRS) III scores in the clinic and reduced beta oscillations during blinded testing in the home setting. Thus, we demonstrated that the novel PI aDBS may enhance chronic, symptomatic treatment of PD.</p>