Bidirectional Prediction of Gait Kinetics and Sagittal Joint Angles During Walking: A Participant-Independent Multi-Study Evaluation

Background: Predicting gait waveforms from reduced measurements requires validation on participants and studies excluded from training. Methods: Two separately fitted tasks were evaluated in adult treadmill walking: body mass and sagittal joint angles predicted single-limb ground reaction forces (GRFs) and joint moments (Task 1; 340 observations, 32 participants, three studies), and GRFs predicted sagittal joint angles (Task 2; 361 observations, 39 participants, four studies). All Kim data were excluded from Task 1 because measured participant masses were unavailable; 21 zero-filled running records were excluded from Task 2. Source waveforms and participant identities were reconstructed before analysis. SVR-RBF, random forest and MLP-ANN underwent participant-grouped hyperparameter searches with training-only input and target scaling inside five-fold participant-independent cross-validation. Leave-one-study-out evaluation tested source transfer. Results: The inner-selected procedure produced Task 1 RMSEs of 0.060 and 0.018 BW for vertical and anterior–posterior GRFs, and 0.212, 0.228 and 0.260 N m/kg for ankle, knee and hip moments. Task 2 RMSEs were 7.01°, 9.76° and 9.74° for ankle, knee and hip angles. Mean channel-normalized errors were 0.380 and 0.496; leave-one-study-out values ranged from 0.440 to 0.996 and 0.441 to 1.426, respectively. Conclusions: Performance depended on outcome, tested configuration and evaluation population. These results characterize adult gait prediction; clinical, overground and prospective independent-cohort performance remain untested.