A machine learning model with only two features can accurately classify lifting height and weight based on forearm and pelvis kinematics

Machine learning was applied to whole-body kinematics collected during a standardized lifting task to predict lifting start and end height and weight lifted. The resulting models included features of the forearm and pelvis segments, and resulted in accurate classification rates between 83% and 98%.