Markerless gait analysis for children and adolescents with juvenile idiopathic arthritis using a machine learning pipeline
Authors' conclusion
The proposed single-camera, markerless pipeline can provide reliable and valid gait data using standard video equipment in children. Differences in gait patterns between JIA patients and TD peers were generally small, likely due to effective disease control.
Study context
- Population
- Children and adolescents with Juvenile Idiopathic Arthritis (JIA) and typically developing peers, age 1.8–17.4 years12 in validation subset
- Participants
- 108 children
- Comparison
- JIA with lower-extremity involvement vs typically developing peers; markerless vs marker-based gait analysis
- JIAn = 60
- Typically developing (TD)n = 48reference
- Outcome
- Feasibility and validity of markerless gait analysis vs marker-based systems
Methodological detailsmarkerless single-camera gait analysis, machine learning pipeline, validation against marker-based motion capture, Statistical Parametric Mapping
- Markerless single-camera gait analysis
- Machine learning pipeline
- Validation against marker-based motion capture
- Statistical Parametric Mapping
Performance
As reported in the abstract
Agreement of markerless vs marker-based joint movement patterns
- Robust agreement between joint movement patterns of the markerless and the marker-based approach
Further findings
| Outcome | JIA | TD |
|---|---|---|
| Knee range of motion, JIA with active arthritis vs TD, across all age groupsJIA value refers to patients with active arthritis | 46.3 | 49.8 |
Joint angle trajectories between groups
- Differences between groups remained limited overall
Original publication
Markerless gait analysis for children and adolescents with juvenile idiopathic arthritis using a machine learning pipeline. Pediatr Rheumatol Online J. Published 28 April 2026. doi:10.
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