Data-driven Characterization of Human Interaction for Model-based Control of Powered Prostheses
Rachel Gehlhar,Yuxiao Chen,Aaron D. Ames,Rachel Gehlhar,Yuxiao Chen,Aaron D. Ames
This paper proposes a data-driven method for powered prosthesis control that achieves stable walking without the need for additional sensors on the human. The key idea is to extract the nominal gait and the human interaction information from motion capture data, and reconstruct the walking behavior with a dynamic model of the human-prosthesis system. The walking behavior of a human wearing a power...
