Search Results for author:
Found 2 papers, 2 papers with code
Predicting knee adduction moment response to gait retraining with minimal clinical data
Insights learned from a ground-truth dataset with both baseline and toe-in gait trials (N = 12) enabled the creation of a large (N = 138) synthetic dataset for training the predictive model.
Estimation of kinematics from inertial measurement units using a combined deep learning and optimization framework
Careful sensor-to-segment alignment and calibration strategies are also necessary, which may burden users and lead to further error in uncontrolled settings.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
