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

机译:基于实际EMG驱动模型的膝关节康复机器人辅助运动训练的实验研究

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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.
机译:本文提出了两个基于实际EMG驱动模型的膝关节康复的机器人辅助运动培训方法,旨在通过神经晕船过程有益地利用患者的能力。 EMG驱动的模型是肌肉骨骼系统的简化表示,具有可接受的精度,以预测膝关节的肌肉力和主动扭矩。因此,可以通过导纳控制器将患者的自愿贡献引入控制回路。初步实验验证了模型预测性能是否能够实时地反映受试者的运动意图,并帮助受试者使用下肢康复机器人进行运动训练。在运动培训期间记录的信息可能有助于了解恢复过程,并对患者的运动能力进行定量评估。

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