Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada.
IEEE Trans Biomed Eng. 2012 Oct;59(10):2913-21. doi: 10.1109/TBME.2012.2213339. Epub 2012 Aug 15.
Estimates of joint or limb impedance are commonly used in the study of how the nervous system controls posture and movement, and how that control is altered by injury to the neural or musculoskeletal systems. Impedance characterizes the dynamic relationship between an imposed perturbation of joint position and the torques generated in response. While there are many practical reasons for estimating impedance rather than its inverse, admittance, it is an acausal representation of the limb mechanics that can lead to difficulties in interpretation or use. The purpose of this study was to explore the acausal nature of nonparametric estimates of joint impedance representations to determine how they are influenced by common experimental and computational choices. This was accomplished by deriving discrete-time realizations of first- and second-order derivatives to illustrate two key difficulties in the physical interpretation of impedance impulse response functions. These illustrations were provided using both simulated and experimental data. It was found that the shape of the impedance impulse response depends critically on the selected sampling rate, and on the bandwidth and noise characteristics of the position perturbation used during the estimation process. These results provide important guidelines for designing experiments in which nonparametric estimates of impedance will be obtained, especially when those estimates are to be used in a multistep identification process.
关节或肢体阻抗的估计常用于研究神经系统如何控制姿势和运动，以及神经或肌肉骨骼系统损伤如何改变这种控制。阻抗描述了关节位置施加的强迫扰动与响应产生的扭矩之间的动态关系。虽然有许多实际原因需要估计阻抗而不是其逆导纳，但它是肢体力学的非因果表示，可能导致解释或使用上的困难。本研究旨在探讨关节阻抗表示的非因果性质，以确定它们如何受到常见实验和计算选择的影响。这是通过推导一阶和二阶导数的离散时间实现来完成的，以说明阻抗脉冲响应函数物理解释中的两个关键困难。这些说明使用模拟和实验数据提供。结果发现，阻抗脉冲响应的形状严重依赖于所选的采样率，以及在估计过程中使用的位置扰动的带宽和噪声特性。这些结果为设计将获得阻抗的非参数估计的实验提供了重要指导，特别是当这些估计将用于多步识别过程时。
