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首页> 外文期刊>Journal of the Chinese Society of Mechanical Engineers, Series C: Transactions of the Chinese Society of Mechanical Engineers >Torque Control by EMG Feedback in Normal and Stroke Subjects Performing Ankle Angle Tracking with a Rehabilitation Robot
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Torque Control by EMG Feedback in Normal and Stroke Subjects Performing Ankle Angle Tracking with a Rehabilitation Robot

机译:肌电图反馈在正常和中风受试者中通过康复机器人进行踝关节角度跟踪的扭矩控制

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摘要

The goal of this study was to investigate the eligibility of using surface electromyography (EMG) as a feedback signal for ankle torque control in both normal and stroke subjects performing ankle joint angle tracking with a rehabilitation robot. The potential advantage of using EMG as an estimator of active torque is direct facilitation of torque control of individual muscle. A fuzzy PD+I controller was implemented to control the robot. A static EMG-torque map was constructed at 5 ankle positions experimentally for each subject. The map was interpolated to estimate the active dorsiflexion torque exerted on the ankle from the EMG of tibialis anterior muscle. Both EMG and the output of the torque sensor were acquired and a weighting factor was used to adjust the relative contribution from these two signals for controlling the robot. Six normal subjects and seven stroke patients were recruited. The angle trajectory to be tracked was alternating ramps (3 degrees/s) of dorsiflexion and plantarflexion. The results showed that all the tested combinations of EMG and the torque sensor signal could be used as the feedback signal for torque control during angle tracking with the robot. The normal subjects had a better performance than the stroke patients and the tracking performance was better when only the signal from the torque sensor was used.
机译:这项研究的目的是调查使用表面肌电图(EMG)作为正常和卒中受试者通过康复机器人进行踝关节角度跟踪的踝关节扭矩控制的反馈信号的资格。使用EMG作为主动扭矩的估算器的潜在优势是直接促进了单个肌肉的扭矩控制。模糊PD + I控制器被实现来控制机器人。为每个受试者实验在5个脚踝位置构建了静态EMG扭矩图。对该图进行插值,以估算胫骨前肌的肌电图施加在脚踝上的主动背屈扭矩。同时获取了EMG和扭矩传感器的输出,并使用加权因子来调整这两个信号的相对贡献,以控制机器人。招募了六名正常受试者和七名中风患者。要跟踪的角度轨迹是背屈和plant屈的交替斜坡(3度/ s)。结果表明,EMG和扭矩传感器信号的所有测试组合都可用作与机器人进行角度跟踪期间扭矩控制的反馈信号。正常受试者的表现优于中风患者,仅使用来自扭矩传感器的信号时,追踪表现也更好。

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