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Bayesian Optimization of DBS for Gait

Study acronym: BOG DBS
StatusRecruiting
PhaseEarly Phase 1
Started
View on ClinicalTrials.gov ↗

Record History

  1. Start date pushed from Sep 2026 to Dec 2026
  2. Study First Submitted
  • Stopped: an ongoing trial was terminated, suspended or withdrawn.
  • Notable: the trial’s plan changed such as a big move in its timeline or size, a new primary endpoint, sponsor or phase, or recruiting opened or resumed.
  • Minor: routine progress and housekeeping, such as sites added or enrollment closed.
This project aims to establish the feasibility of Bayesian optimization for tuning deep brain stimulation (DBS) to treat gait symptoms in Parkinson's disease (PD) patients. Our primary question is: Can Bayesian optimization of DBS achieve reproducible results within a feasible number of gait measurements? PD patients will be enrolled who have DBS of the subthalamic nucleus (STN) or globus pallidus (GP) in whom at least 3 months have passed since activation of their neurostimulators, for stabilization of clinical stimulator settings. We will apply Bayesian optimization to derive DBS settings which maximally lengthen step length relative to the OFF DBS state.
Trial Details
NCT Number NCT07835308
Lead Sponsor University of Minnesota
Conditions
(from sponsor)		 Parkinson Disease (PD)
Related terms Parkinson Disease
Enrollment 15 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov