首页> 外文会议>IEEE International Conference on Robotics and Biomimetics >Active tracking movements of flexion and extension on the elbow joint for an initial prototype of EMG-driven assistant exoskeleton
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Active tracking movements of flexion and extension on the elbow joint for an initial prototype of EMG-driven assistant exoskeleton

机译:EMG驱动辅助外骨骼初始原型的弯头弯曲和伸展的积极跟踪运动

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Various exoskeletons have been developed for the assistance of upper and lower limbs rehabilitation, however, therapists and doctors have pointed out that passive-repeating motions of limbs is ineffective in terms of neurological recovery. To improve the neurological recovery of human motor control, active-assisted encouragement as therapist and doctors manually provided should also be simulated with help of exoskeleton targeting for rehabilitative purpose. In this paper, a single-degree-of-freedom (SDOF) robotic joint to mimic elbow movements is developed and EMG signals are collected using as a bio-feedback signal. A pair of muscles including biceps and triceps that involved in flexion and extension on the elbow joint are selected, acquisition and processing of EMG signals is then achieved by designed hardware filtering and proposed software algorithms. By analysis of the resultant EMG signals, the intentions of flexion and extension movements are quantitatively presented. Online control commands for the exoskeleton are then spontaneously produced. A close-loop control with EMG-driven in real time is applied on an initial prototype of human-machine interface (HMI) for an active assistance using the exoskeleton. Initial applications on the experimental prototype have proved the effectiveness of the proposed active tracking method that has successfully tracking effort that bridge the wearer and the wearable exoskeleton together.
机译:已经开发了各种外骨骼,用于上下肢体康复的援助,然而,治疗师和医生指出,在神经恢复方面,肢体的被动重复运动无效。为了改善人机控制的神经系统恢复,还应利用外骨骼靶向恢复目的的脑骨骼靶向来模拟作为治疗师和医生的主动辅助鼓励。在本文中,开发了一种自由度(SDOF)机器人接头以模拟弯头运动,并使用EMG信号作为生物反馈信号收集。选择了一对肌肉,包括二头肌和三头肌,其参与弯曲和肘关节上的屈曲和延伸,然后通过设计的硬件滤波和提出的软件算法来实现EMG信号的采集和处理。通过分析所得的EMG信号,量化屈曲和延伸运动的意图。然后自发地生产外骨骼的在线控制命令。使用Exoskeleton的人机界面(HMI)的初始原型应用了EMG驱动的闭环控制,用于使用外骨架的主动辅助。实验原型上的初始应用已经证明了提出的主动跟踪方法的有效性,该方法已成功跟踪将穿着者和可穿戴外骨骼桥的努力桥接在一起。

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