Model-based fuzzy adaptation for control of a lower extremity rehabilitation exoskeleton

Different gait patterns of stroke patients cannot be derived satisfactorily by traditional treadmill training robots. This paper presents a method to generate adaptive trajectories for controlling a lower extremity rehabilitation exoskeleton designed to help patients recover or improve walking ability. The model-based adaptation mechanism that consists of an inverse dynamic model, a trajectory generator and a fuzzy adaptation algorithm is proposed to minimize patient´s discomfort when active muscle contractions are not easily to be obtained. The effectiveness of the fuzzy adaptation algorithm, which accounts for the experience of a rehabilitation doctor, is demonstrated numerically with an illustrative example in this paper.