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In the process of robot-assisted training for upper limb rehabilitation, a passive training strategy is usually used for stroke patients with flaccid paralysis. In order to stimulate the patient's active rehabilitation willingness, the rehabilitation therapist will use the robot-assisted training strategy for patients who gradually have the ability to generate active force. This study proposed a motor function assessment technology for human upper-limb based on fuzzy recognition on interaction force and human-robot interaction control strategy based on assistance-as-needed. A passive training mode based on the calculated torque controller and an assisted training mode combined with the potential energy field were designed, and then the interactive force information collected by the three-dimensional force sensor during the training process was imported into the fuzzy inference system, the degree of active participation
Li et al. (Sun,) studied this question.