What not to wear: Examining the usability of markerless motion capture for pediatric populations.
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- Record sourced from PubMed, PMID 42105411.
- Also identified by DOI 10.1016/j.jbiomech.2026.113349.
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Abstract
Markerless motion capture may improve the accessibility and participants experience of three-dimensional gait analysis in children. This study explores aspects of usability of markerless motion capture that have not been previously studied specifically, the consequences of street clothing on lower-limb kinematics, participant and caregiver perceptions, and assessment durations. Thirty typically developing children completed two 3D gait analysis protocols. They wore either a) "Conventional" clothing required for marker-based methods and had markers placed, or b) their "Street" clothes without markers. Markerless gait kinematics were measured using Theia3D. Root-mean-square-deviations (RMSD) and an outlier analysis were used to determine differences between experimental conditions. Differences in participant perceptions were assessed using custom surveys, and differences in testing duration were assessed using the Wilcoxon Signed Rank test. Median RMSDs were < 4° and maximal RMSDs were 3.6°-16.0° and with no consistent pattern across joints and planes of motion, suggesting minimal differences between clothing conditions. Individuals with larger deviations generally wore baggy or loose clothing. When asked which condition they would prefer to repeat, 12% (n = 3/25) indicated the Conventional condition, 68% (n = 17/25) mentioned the Street condition and 16% (n = 4/25) would repeat both. Further, caregivers more frequently reported atypical gait in the Conventional condition. The Street condition took less time with a median (25th-75th percentile) difference of 11 (9-13) minutes (p < 0.001). Street clothing with minimal restrictions can be used without compromising lower-limb kinematics, while improving participant experience and reducing assessment duration. These findings may contribute to improved access to 3D gait analysis.