Predicting knee adduction moment response to gait retraining with minimal clinical data
Fig 5
Prediction of KAM reduction using synthetic training data (Calgary Running Injury Clinic dataset).
Synthetic toe-in data from 108 subjects were used to train the predictive model, which achieved an MAE of 0.0826 (± 0.0628) %BW*HT on the test set of 15 subjects. The line of best fit (dashed line) has an R2 of 0.87. The signed errors (the difference between actual and predicted KAM reduction) of the training and test sets were similarly distributed around zero.