Study of human forearm posture maintenance with a physiologically based robotic arm and spinal level neural controller
Study of human forearm posture maintenance with a physiologically based robotic arm and spinal level neural controller
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基于生理学的机械臂和脊柱神经控制器维持人类前臂姿势的研究
DOI：
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发表时间：
1997
影响因子：
1.9
通讯作者：
B. Hannaford
中科院分区：
文献类型：
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作者：
C. Chou;B. Hannaford
摘要： 本研究的目标是：（1）将人类神经-肌肉-骨骼运动控制的知识应用于生物力学设计的、神经控制的“仿人”机器人手臂系统，（2）证明这样的系统能够在可比较的实验中相当好地匹配人类手臂的响应，（3）利用仿人手臂系统研究一些有争议的问题，预测人体运动控制系统的新现象。一个生理学上类似的人工神经网络控制器和一个解剖学上精确的机器人测试肘应用在这项研究中。为了使物理肘系统具有尽可能接近人类手臂的机械性能，McKibben气动人工肌肉，力传感器和机械肌梭集成在系统中，具有解剖学上精确的肌肉附着点。一个生理学上类似的，人工神经网络控制器被用来模拟脊髓节段反射电路，包括Ia和Ib传入反馈的行为。进行了系统的肘关节姿势保持实验，并与生理实验数据进行了比较。新的实验中，扭矩扰动的反应进行测量时，选定的传入通路被阻断。介绍了“协方差图”。采用线性模型分析系统各组成部分的作用。结果表明，肌肉的共同收缩和Ia传入与γ动态运动神经元的兴奋是两个有效的方式来增加关节的刚度和阻尼，这反过来又降低了关节的机械敏感性的外部扰动，缩短系统的建立时间。
Abstract. The goals of this research are: (1) to apply knowledge of human neuro-musculo-skeletal motion control to a biomechanically designed, neural controlled, ‘anthroform’ robotic arm system, (2) to demonstrate that such a system is capable of responses that match those of the human arm reasonably well in comparable experiments, and (3) to utilize the anthroform arm system to study some controversial issues and to predict new phenomena of the human motion control system. A physiologically analogous artificial neural network controller and an anatomically accurate robotic testing elbow are applied in this study. In order to build the physical elbow system to have mechanical properties as close as possible to the human arm, McKibben pneumatic artificial muscles, force sensors, and mechanical muscle spindles are integrated in the system with anatomically accurate muscle attachment points. A physiologically analogous, artificial neural network controller is used to emulate the behavior of spinal segmental reflex circuitry including Ia and Ib afferent feedbacks. Systematic experiments of elbow posture maintenance are performed and compared with physiological experimental data. New experiments are performed in which responses to torque perturbation are measured when selected afferent pathways are blocked. A ‘covariance diagram’ is introduced. And a linear model is used to help to analyze the roles of system components. The results show that muscle co-contraction and Ia afference with gamma dynamic motoneuron excitation are two efficient ways to increase joint stiffness and damping, which in turn reduces the mechanical sensitivity of the joint to external perturbation and shortens the settling time of the system.
皮质运动神经元和红质运动神经元细胞群对前肢肌肉活动的控制。
影响因子：
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作者：
Fetz,EE;Cheney,PD;Mewes,K;Palmer,S
通讯作者：
Palmer,S