ArticleNature communications2024
A machine learning contest enhances automated freezing of gait detection and reveals time-of-day effects.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed.
- Crowdsourcing and machine learning contests in Parkinson's disease research - when do they work?Journal of Parkinson's disease · 2026Review
- Deep learning for freezing of gait assessment using inertial measurement units: a multicentre validation study.NPJ Parkinson's disease · 2026Article
- Integrating Eye Tracking and Inertial Sensing for Enhanced Freezing of Gait Detection in Parkinson's Disease.The European journal of neuroscience · 2026Article
- Freezing of Gait in Parkinson's Disease: A Scoping Review on the Path Towards Real-Time Therapies.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
- Deep Learning for Freezing of Gait Detection: Cross-Dataset Validation Reveals Critical Deployment Gaps Between Laboratory and Daily Living Wearable Monitoring.Sensors (Basel, Switzerland) · 2026Article
- Deep neurobehavioral phenotyping uncovers neural fingerprints of locomotor deficits in Parkinson's disease.NPJ Parkinson's disease · 2026Article
- Beyond the Leaderboard: Evaluating the Robustness of Deep Learning Models for Detecting Freezing of Gait.The European journal of neuroscience · 2026Article
- Mantis Leg-Inspired Smart Insole Integrating Closed-Loop Power Supply for Advanced Wearable Gait Diagnostics.Research (Washington, D.C.) · 2026Article
- Distinguishing Gait Patterns in PD Patients Under Different Treatments via Recurrence Plots and Vision Transformer Fusion.IEEE open journal of engineering in medicine and biology · 2026Article
- Digital Phenotyping of Sensation Seeking: A Machine Learning Approach Using Gait Analysis.Behavioral sciences (Basel, Switzerland) · 2025Article
- Artificial Intelligence-Driven Neuromodulation in Neurodegenerative Disease: Precision in Chaos, Learning in Loss.Biomedicines · 2025Review
- Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait.Journal of medical Internet research · 2025Article
- Could adaptive deep brain stimulation treat freezing of gait in Parkinson's disease?Journal of neurology · 2025Review
- Freezing of gait detection: The effect of sensor type, position, activities, datasets, and machine learning model.Journal of Parkinson's disease · 2025Article
- Technology for measuring freezing of gait: Current state of the art and recommendations.Journal of Parkinson's disease · 2025Review
- Home-Based sensing of the nervous system with clinical neurophysiology technologies: IFCN handbook chapter.Clinical neurophysiology practice · 2025Review
- Deep learning techniques for detecting freezing of gait episodes in Parkinson's disease using wearable sensors.Frontiers in physiology · 2025Article
- Toward a unified gait freeze index: a standardized benchmark for clinical and regulatory evaluations.Frontiers in neurology · 2025Article
- Gut-brain axis modulation in remote rehabilitation of Parkinson's disease: reconstructing the fecal metabolome and nigral network connectivity.Frontiers in neurology · 2025Review
Corrections and comments
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Authors and funding
15 authors.
Funding
Abstract
Freezing of gait (FOG) is a debilitating problem that markedly impairs the mobility and independence of 38-65% of people with Parkinson's disease. During a FOG episode, patients report that their feet are suddenly and inexplicably "glued" to the floor. The lack of a widely applicable, objective FOG detection method obstructs research and treatment. To address this problem, we organized a 3-month machine-learning contest, inviting experts from around the world to develop wearable sensor-based FOG detection algorithms. 1,379 teams from 83 countries submitted 24,862 solutions. The winning solutions demonstrated high accuracy, high specificity, and good precision in FOG detection, with strong correlations to gold-standard references. When applied to continuous 24/7 data, the solutions revealed previously unobserved patterns in daily living FOG occurrences. This successful endeavor underscores the potential of machine learning contests to rapidly engage AI experts in addressing critical medical challenges and provides a promising means for objective FOG quantification.
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Registered trials
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.