Lower body kinematics estimation from wearable sensors for walking and running: A deep learning approach.
Journal:
Gait & posture
PMID:
33161275
Abstract
BACKGROUND: Inertial measurement units (IMUs) are promising tools for collecting human movement data. Model-based filtering approaches (e.g. Extended Kalman Filter) have been proposed to estimate joint angles from IMUs data but little is known about the potential of data-driven approaches.