ArticleNeurological research and practice2023
Subthalamic 85 Hz deep brain stimulation improves walking pace and stride length in Parkinson's disease patients.
Article in Neurological research and practice, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Efficacy of subthalamic deep brain stimulation programming strategies for gait disorders in Parkinson's disease: a systematic review and meta-analysis.Neurosurgical review · 2024Pooled it
- Stimulation settings in subthalamic nucleus deep brain stimulation for parkinson's disease - a retrospective single-center observational study.Neurological research and practice · 2026Article
- Using explainable AI to identify disease-relevant and deep brain stimulation treatment-sensitive gait features in Parkinson's disease.Journal of neuroengineering and rehabilitation · 2026Article
- At-home movement state classification using totally implantable cortical-basal ganglia neural interface.Science advances · 2026Article
- Influence of Rehabilitation Aid Use on Obstacle Height During Gait in Patients with Foot Drop: A Case Series Study.Healthcare (Basel, Switzerland) · 2025Article
- Differential Effects of Levodopa and Stimulation on Post-Surgery Freezing of Gait in Subthalamic Nucleus Deep Brain Stimulation Parkinson's Disease Patients: A Clinical and Kinematic Analysis.Movement disorders clinical practice · 2025Article
- Multidisciplinary inpatient care for Parkinson's disease: a single-centre cohort study on improvements in gait, overall motor function, and quality of life.Neurological research and practice · 2025Article
- Modeling and optimizing deep brain stimulation to enhance gait in Parkinson's disease: personalized treatment with neurophysiological insights.NPJ Parkinson's disease · 2025Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMobile gait sensors represent a compelling tool to objectify the severity of symptoms in patients with idiopathic Parkinson's disease (iPD), but also to determine the therapeutic benefit of interventions. In particular, parameters of Deep Brain stimulation (DBS) with its short latency could be accurately assessed using sensor data. This study aimed at gaining insight into gait changes due to different DBS parameters in patients with subthalamic nucleus (STN) DBS.
methodsAn analysis of various gait examinations was performed on 23 of the initially enrolled 27 iPD patients with chronic STN DBS. Stimulation settings were previously adjusted for either amplitude, frequency, or pulse width in a randomised order. A linear mixed effects model was used to analyse changes in gait speed, stride length, and maximum sensor lift.
resultsThe findings of our study indicate significant improvements in gait speed, stride length, and leg lift measurable with mobile gait sensors under different DBS parameter variations. Notably, we observed positive results at 85 Hz, which proved to be more effective than often applied higher frequencies and that these improvements were traceable across almost all conditions. While pulse widths did produce some improvements in leg lift, they were less well tolerated and had inconsistent effects on some of the gait parameters. Our research suggests that using lower frequencies of DBS may offer a more tolerable and effective approach to enhancing gait in individuals with iPD.
conclusionsOur results advocate for lower stimulation frequencies for patients who report gait difficulties, especially those who can adapt their DBS settings remotely. They also show that mobile gait sensors could be incorporated into clinical practice in the near future.
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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 Socratic graph.