Validation, characterization, and utility of markerless motion capture in a large cohort of pediatric patients with complex gait patterns

Markerless motion capture has emerged as a potential substitute for traditional marker-based systems, offering scalable, non-invasive acquisition of human movement. Despite increasing adoption in research and sports applications, its clinical utility for children with complex gait patterns remains an open question. To address this gap, simultaneous marker-based and markerless data were collected in 202 pediatric children (12.1 {+/-} 3.9 years). Marker-based kinematics were processed using the Shriners Childrens Gait Model (SCGM), while markerless outputs were computed using Theia3D with identical Cardan sequences. Agreement between systems was evaluated using statistical parametric mapping (SPM), root-mean-square error (RMSE), and a gait pattern classification based on the plantarflexor-knee extension index. Markerless output systematically underestimated pelvic tilt, hip rotation, and knee rotation and demonstrated reduced between-subject variance in the transverse plane. SPM revealed widespread waveform differences, although most were of negligible effect, especially in the sagittal plane. Mean sagittal-plane RMSEs were < 5{degrees} for the knee and ankle and < 8{degrees} for the pelvis and hip. Coronal-plane deviations were < 7{degrees}, whereas transverse-plane errors exceeded 10{degrees}. RMSE increased significantly with body mass index and use of a walker (p < 0.001). Agreement in sagittal-plane gait classification was moderate between systems ({kappa} = 0.60; 67% overall concordance). These results indicate that markerless motion capture is suitable for analyses emphasizing sagittal deviations but remains limited for applications requiring precise axial or frontal-plane estimation. Future work should address algorithmic underestimation of transverse motion and evaluate markerless performance across increasing severity of gait deviation.