ArticleFrontiers in digital health2025
Validation of markerless video-based gait analysis using pose estimation in toddlers with and without neurodevelopmental disorders.
Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- MACAFNet transformer-based multi-atlas fusion framework for autism spectrum disorder classification using functional connectivity.Scientific reports · 2026Article
- Markerless gait analysis for children and adolescents with juvenile idiopathic arthritis using a machine learning pipeline.Pediatric rheumatology online journal · 2026Article
- Article
- A graphical user interface for editing keypoints from human pose estimation algorithms.medRxiv : the preprint server for health sciences · 2025Article
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Authors and funding
4 authors.
Funding
Abstract
Introduction: The onset of locomotion is a critical motor milestone in early childhood and increases engagement with the environment. Toddlers with neurodevelopmental disabilities often have atypical motor development that impacts later outcomes. Video-based gait analysis using pose estimation offers an alternative to standardized motor assessments which are subjective and difficult to ascertain in some populations, yet very little work has been done to determine its accuracy in young children. To fill this gap, this study aims to assess the feasibility and accuracy of pose estimation for gait analysis in children with a range of developmental levels. Methods: We analyzed the overground gait of 112 toddlers (M: 30 months, SD: 8 months) with and without developmental disabilities using the ProtoKinetics Zeno Walkway system. Simultaneously recorded videos were processed in OpenPose to perform pose estimation and a custom MATLAB workflow to calculate average spatiotemporal gait parameters. Pearson correlations were used to compare OpenPose with the Zeno Walkway for velocity, step length, and step time. A Bland-Altman analysis (difference vs. average) was used to assess the agreement between methodologies and determine the difference of means. Developmental levels were assessed using the Mullen Scales of Early Learning. Results: Our analysis included children with autism ( Discussion: Our results suggest that video-based gait analysis using pose estimation is accurate in toddlers with a range of developmental levels. Video-based gait analysis is low cost and can be implemented for remote data collection in natural environments such as a participant's home. These advantages open possibilities for using repeated measures to increase our knowledge of how gait ability changes over time in pediatric populations and improve clinical screening tools, particularly in those with neurodevelopmental disabilities who exhibit motor impairments.
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Registered trials
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