LAUSR

Patients suffering from neurological and orthopedic diseases or injuries usually have mobility impairment problems, and they require customized rehabilitation training to recover. In recent years, robotic assistive devices have been widely studied for gait rehabilitation. In this paper, methods to determine user-adaptive assistance of assistive knee braces (AKBs) in gait rehabilitation are investigated. A fuzzy expert system, which takes a patient’s physical condition and gait analysis results as inputs, is proposed to configure suitable levels of different assistive functions of the AKB. During gait rehabilitation, the AKB generates a reference knee trajectory according to the patient’s individual gait pattern, and the interaction force is controlled through a hybrid impedance controller considering the individual assistive function configuration. The proposed methods are verified through clinical pilot studies of a patient with lower limb weakness. Experimental results show that AKB with the proposed control strategies can provide effective assistance to improve the patient’s gait performance during gait rehabilitation.