基于人工神经网络的上肢肌肉刚度估计

Ze Cui, Wangyang Han, Dong-Hai Qian, Yumei Wang, Guowen Qiu, Danjie Zhu
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引用次数: 2

摘要

人体上肢是一个灵活的运动器官,可以实现多自由度运动。它可以根据接触对象的刚度变化,做出相应的刚度变化。研究人体肌肉的刚度特性对医疗、服务业和制造业都具有重要意义。本文建立的人工神经网络模型以人体肌肉肌电信号和上肢关节角度作为输入,输出人体关节刚度。该模型为柔性机械臂的遥操作控制提供了理论依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation of upper limb muscle stiffness based on artificial neural network
The human upper limb is a flexible locomotive organ, which can achieve multi-degree of freedom of movement. It can make the corresponding change in stiffness according to the stiffness changes of the contact object. The study of the stiffness properties of human muscles is of great significance to the medical and service industries as well as to the manufacturing industry. The artificial neural network model established in this paper makes the EMG signal of human muscle and the angle of upper limb joint as the input, and the body joint stiffness is output. The model provides a theoretical basis for the teleoperation control of the flexible manipulators.
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