Bayesian Optimization of DBS for Gait

Part of paid clinical trials in Minneapolis, Minnesota.

Sponsor
University of Minnesota
Study ID
NCT07835308
Phase
EARLY_PHASE1
Status
Recruiting
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Conditions

  • Parkinson Disease (PD)

Eligibility Criteria

Sex
ALL
Age
18 Years - N/A
Healthy Volunteers
Not accepted

Interventions

  • Deep Brain Stimulation — OTHER
    DBS within FDA-approved limits and labeling for symptoms of PD

Study Details

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.

Key Dates

First listed
Sep 22, 2026
Start date
Sep 30, 2026
Status verified
Sep 2026
Primary completion
Mar 31, 2031
Completion
Mar 31, 2033

Study Design

Enrollment
15 participants (estimated)
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
BASIC_SCIENCE

Arms

  • Experimental: All participants
    All participants will be allocated to this group for DBS stimulation within FDA-approved limits and labeling for symptoms of PD.

Primary Outcome Measure

Gait Test [ Time Frame: This will be repeated approximately 30 times throughout the study visit (Day 1) on various DBS settings to reach putatively optimal DBS settings. ]

Central Contacts

Locations (1)

FacilityCityStateZIPSite coordinators
University of MinnesotaMinneapolisMinnesota55455
Johanna Caskey, BA
[email protected]
763-353-9470
Scott Cooper, MD, PhD (PRINCIPAL_INVESTIGATOR)

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By research site
University of Minnesota· Minneapolis, MN

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