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.