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由形状记忆合金驱动的上肢康复机器人与功能性电刺激阵列协作以实现抓握训练。

Upper Limb Rehabilitation Robot Powered by PAMs Cooperates with FES Arrays to Realize Reach-to-Grasp Trainings.

作者信息

Tu Xikai, Han Hualin, Huang Jian, Li Jian, Su Chen, Jiang Xiaobo, He Jiping

机构信息

School of Industrial Design, Hubei University of Technology, Wuhan 430068, China

School of Automation, Huazhong University of Science and Technology, Wuhan 430074, China

出版信息

J Healthc Eng. 2017(2017). doi: 10.1155/2017/1282934.

Abstract

The reach-to-grasp activities play an important role in our daily lives. The developed RUPERT for stroke patients with high stiffness in arm flexor muscles is a low-cost lightweight portable exoskeleton rehabilitation robot whose joints are unidirectionally actuated by pneumatic artificial muscles (PAMs). In order to expand the useful range of RUPERT especially for patients with flaccid paralysis, functional electrical stimulation (FES) is taken to activate paralyzed arm muscles. As both the exoskeleton robot driven by PAMs and the neuromuscular skeletal system under FES possess the highly nonlinear and time-varying characteristics, iterative learning control (ILC) is studied and is taken to control this newly designed hybrid rehabilitation system for reaching trainings. Hand function rehabilitation refers to grasping. Because of tiny finger muscles, grasping and releasing are realized by FES array electrodes and matrix scan method. By using the surface electromyography (EMG) technique, the subject's active intent is identified. The upper limb rehabilitation robot powered by PAMs cooperates with FES arrays to realize active reach-to-grasp trainings, which was verified through experiments.

摘要

伸手抓握动作在我们的日常生活中起着重要作用。为患有手臂屈肌高刚度的中风患者开发的RUPERT是一种低成本、轻便的便携式外骨骼康复机器人,其关节由气动人工肌肉(PAM)单向驱动。为了扩大RUPERT的适用范围,特别是对于弛缓性麻痹患者,采用功能性电刺激(FES)来激活麻痹的手臂肌肉。由于由PAM驱动的外骨骼机器人和FES下的神经肌肉骨骼系统都具有高度非线性和时变特性,因此研究了迭代学习控制(ILC)并将其用于控制这个新设计的用于伸展训练的混合康复系统。手部功能康复指的是抓握。由于手指肌肉微小,通过FES阵列电极和矩阵扫描方法实现抓握和松开。通过使用表面肌电图(EMG)技术,识别受试者的主动意图。由PAM驱动的上肢康复机器人与FES阵列配合,实现主动伸手抓握训练,这已通过实验得到验证。

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