A robotic manipulator for the characterization of two-dimensional dynamic stiffness using stochastic displacement perturbations
A robotic manipulator for the characterization of two-dimensional dynamic stiffness using stochastic displacement perturbations
复制标题
使用随机位移扰动表征二维动态刚度的机器人操纵器
DOI：
10.1016/s0165-0270(00)00307-1
复制
发表时间：
2000
影响因子：
3
通讯作者：
E. Perreault
中科院分区：
文献类型：
--
作者：
A. M. Acosta;R. Kirsch;E. Perreault
已经开发了用于在宽范围的条件下估计人臂的二维动态刚度的实验技术。已经开发了一种机器人操纵器来创建负载，受试者执行各种任务，并对手臂的端点施加扰动，以估计其机械性能。机械手可以产生静态端点力超过220 N，在任何方向上的运动平面，这个平面可以垂直平移和倾斜在很大范围内研究手臂动态刚度在许多功能相关的平面。它可以施加随机的位置和力的扰动，其带宽超过的手臂。这些随机扰动避免不良的意志反应，并允许使用短时间的实验测试的刚度动态的有效估计。使用几个二维物理系统，其属性是独立的特点，这个机械手的能力，以表征惯性粘弹性系统进行了测试。作为一个例子，使用的机械手在研究上肢力学性能的端点动态刚度特性估计的人的手臂。这些方法的系统特性，其特征在于将是有用的，在探测正常的神经手臂控制策略，并在开发康复干预措施，以改善残疾人的手臂运动。
Experimental techniques for estimating the two-dimensional dynamic stiffness of the human arm over a wide range of conditions have been developed. A robotic manipulator has been developed to create loads against which subjects perform various tasks and also to impose perturbations onto the endpoint of the arm to allow estimation of its mechanical properties. The manipulator can produce static endpoint forces exceeding 220 N in any direction in its plane of motion, and this plane can be vertically translated and tilted over wide ranges to study arm dynamic stiffness in many functionally relevant planes. It can impose stochastic position and force perturbations whose bandwidth exceeds that of the arm. These random perturbations avoid undesirable volitional reactions and allow the efficient estimation of stiffness dynamics using experimental trials of short duration. The ability of this manipulator to characterize inertial-viscoelastic systems was tested using several two-dimensional physical systems whose properties were independently characterized. The endpoint dynamic stiffness properties of a human arm were estimated as an example of the use of the manipulator in studying upper limb mechanical properties. The system properties characterized by these methods will be useful in probing normal neural arm control strategies and in developing rehabilitation interventions to improve arm movements in disabled individuals.