ArticleNPJ digital medicine2025
N2GNet tracks gait performance from subthalamic neural signals in Parkinson's disease.
Article in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Activity-dependent adaptive deep brain stimulation improves gait in Parkinson's disease.Nature medicine · 2026Article
- N2G calibrator: a cross-subject adversarial learning framework for neural signal-driven gait tracking in Parkinson's disease.Communications engineering · 2026Article
- Local field potential biomarkers for adaptive deep brain stimulation in Parkinson's disease: A scoping review.Surgical neurology international · 2026Review
- Closing the loop in DBS: A data-driven approach.Parkinsonism & related disorders · 2025Review
- Could adaptive deep brain stimulation treat freezing of gait in Parkinson's disease?Journal of neurology · 2025Review
- An initial machine learning model applied to local field potential data from the subthalamic nucleus to detect freezing of gait in Parkinson's disease.Frontiers in neurologyArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Adaptive deep brain stimulation (DBS) provides individualized therapy for people with Parkinson's disease (PWP) by adjusting the stimulation in real-time using neural signals that reflect their motor state. Current algorithms, however, utilize condensed and manually selected neural features which may result in a less robust and biased therapy. In this study, we propose Neural-to-Gait Neural network (N2GNet), a novel deep learning-based regression model capable of tracking real-time gait performance from subthalamic nucleus local field potentials (STN LFPs). The LFP data were acquired when eighteen PWP performed stepping in place, and the ground reaction forces were measured to track their weight shifts representing gait performance. By exhibiting a stronger correlation with weight shifts compared to the higher-correlation beta power from the two leads and outperforming other evaluated model designs, N2GNet effectively leverages a comprehensive frequency band, not limited to the beta range, to track gait performance solely from STN LFPs.
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Registered trials
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