Control of Wearable Walking Support System Based on Human-Model and GRF

Abstract

In this paper, a wearable walking support system for people who have difficulties in walking because of weakened lower extremities is proposed. We propose a model-based control algorithm for the wearable device without using biological signals, that is, the knee joint support moment is calculated as a function of the user’s posture and the GRF based on the gravity term and GRF term of the necessary knee joint moment, which is estimated based on a human model. The control algorithm is implemented in the wearable walking support device, referred to as Wearable Walking Helper-II, for supporting antigravity muscles on lower extremities, and experimental results illustrate the potential of the proposed system.