Experimental study of robot-assisted exercise training for knee rehabilitation based on a practical EMG-driven model

Long Peng, Z. Hou, Liang Peng, Weiqun Wang
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引用次数: 14

Abstract

This paper proposes two robot-assisted exercise training methods for knee rehabilitation based on a practical EMG-driven model, aiming to beneficially exploit the patient's ability through neurorehabilitation process. The EMG-driven model is a simplified representation of the musculoskeletal system, with acceptable accuracies to predict the muscle forces and active torque of knee joint. Thus the patient's voluntary contribution can be introduced to the control loop through admittance controller. Preliminary experiments verify that the model prediction performance is able to reflect the subjects' motion intention in real-time and assist the subjects to perform exercise training with a lower limb rehabilitation robot. The information recorded during exercise training could be useful to understand the process of recovery and make quantitative evaluations to the patient's motor abilities.
基于肌电驱动模型的机器人辅助膝关节康复运动训练实验研究
本文提出了两种基于实用肌电驱动模型的机器人辅助膝关节康复运动训练方法,旨在通过神经康复过程有益地开发患者的能力。肌电驱动模型是肌肉骨骼系统的简化表示,具有可接受的精度来预测膝关节的肌肉力和主动扭矩。因此,患者的自愿贡献可以通过导纳控制器引入控制回路。初步实验验证,该模型预测性能能够实时反映受试者的运动意图,辅助受试者使用下肢康复机器人进行运动训练。在运动训练过程中记录的信息有助于了解患者的恢复过程,并对患者的运动能力进行定量评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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