Megan R. Ebers

This paper develops a deep learning method to reconstruct dense human motion data from sparse sensors, enabling accurate tracking of unmonitored body segments and improving digital biomarker estimates.

This study uses neural networks to quantify individual gait responses to ankle exoskeletons by modeling discrepancies between nominal and exoskeleton gait data.