ArticleFrontiers in human neuroscience2023
Unraveling the complexities of programming neural adaptive deep brain stimulation in Parkinson's disease.
Article in Frontiers in human neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Chronic adaptive deep brain stimulation versus conventional stimulation in Parkinson's disease: a blinded randomized feasibility trial.Nature medicine · 2024Trial
- Real-Time ECG Artifact Removal for Adaptive Deep Brain Stimulation: A Comparative Study.Sensors (Basel, Switzerland) · 2026Article
- Real-Time Kinematic Adaptive Deep Brain Stimulation Safely Reduces Gait Impairment and Freezing of Gait in Parkinson's Disease.medRxiv : the preprint server for health sciences · 2026Article
- Advanced Therapeutics in Parkinson's Disease: What's New?Current neurology and neuroscience reports · 2026Review
- Subthalamic Electrophysiological Mapping of Gait Initiation Dynamics and Freezing in Parkinson's Disease.Annals of neurology · 2025Article
- Patient, target, device, and program selection for DBS in Parkinson's disease: advancing toward precision care.NPJ Parkinson's disease · 2025Review
- Closing the loop in DBS: A data-driven approach.Parkinsonism & related disorders · 2025Review
- Beta burst-driven adaptive deep brain stimulation for gait impairment and freezing of gait in Parkinson's disease.Brain communications · 2025Article
- Subthalamic nucleus input-output dynamics are correlated with Parkinson's burden and treatment efficacy.NPJ Parkinson's disease · 2024Article
- Current and future applications of local field potential-guided programming for Parkinson's disease with the Percept™ rechargeable neurostimulator.Neurodegenerative disease management · 2024Review
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Authors and funding
4 authors.
Funding
Abstract
Over the past three decades, deep brain stimulation (DBS) for Parkinson's disease (PD) has been applied in a continuous open loop fashion, unresponsive to changes in a given patient's state or symptoms over the course of a day. Advances in recent neurostimulator technology enable the possibility for closed loop adaptive DBS (aDBS) for PD as a treatment option in the near future in which stimulation adjusts in a demand-based manner. Although aDBS offers great clinical potential for treatment of motor symptoms, it also brings with it the need for better understanding how to implement it in order to maximize its benefits. In this perspective, we outline considerations for programing several key parameters for aDBS based on our experience across several aDBS-capable research neurostimulators. At its core, aDBS hinges on successful identification of relevant biomarkers that can be measured reliably in real-time working in cohesion with a control policy that governs stimulation adaption. However, auxiliary parameters such as the window in which stimulation is allowed to adapt, as well as the rate it changes, can be just as impactful on performance and vary depending on the control policy and patient. A standardize protocol for programming aDBS will be crucial to ensuring its effective application in clinical practice.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.