Biomechanics-Embedded Deep Learning for Joint Moment Estimation in Clinical Gait Analysis for Cerebral Palsy: A Learnable Hill-Type Pathway.

Accurate lower-limb joint moment estimation is essential for clinical gait analysis in children with cerebral palsy (cerebral palsy), yet conventional methods require force plates for ground reaction force (ground reaction force) measurement, limiting assessment to specialized laboratories.

Joint-angle sequences are encoded by a Transformer and sEMG signals by a graph encoder.

Before self-distillation, the model achieved a pearson correlation coefficient of 0.824, compared with 0.771 for the best of 12 capacity-matched baselines.