片麻痺患者用歩行訓練リハビリテーションロボットにおける強化学習を用いたアシスト量自動調整システムの開発

Abstract

We have developed a gait training rehabilitation robot “Akita Trainer” for hemiplegic patients. It has servomotors attached to the hip and knee joints of the exoskeleton, and driving it enables gait rehabilitation of the paralyzed people. As its core systems, we developed a variable assist system and an automatic assist adjustment system. The variable assist system based on compliance control can change the stiffness parameter of “Akita Trainer” to provide assist torque according to the degree of paralysis. The automatic assist adjustment system uses reinforcement learning to change the stiffness parameter to the optimal value for the paralyzed people while using this robot. We conducted an experiment with three healthy subjects to validate the combined system of both. We set up two walking patterns: , normal walking and pseudo-hemiplegic walking assuming right hemiplegia. The participants walked for 10 minutes on the treadmill at a speed of 0.8 km/h. The amount of assistance decreased for normal walking and increased for pseudo-hemiplegic walking, indicating that the optimal amount of assistance can be provided according to the walking patterns. By using this system, it is possible to perform gait rehabilitation with the optimal assist torque for the hemiplegic people.