A geometric framework for the estimation of joint stiffness of the human wrist*

D. Formica, Muhammad Azhar, Paolo Tommasino, D. Campolo
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引用次数: 4

Abstract

Estimating joint stiffness is of paramount importance for studying human motor control and for clinical assessment of neurological diseases. Usually stiffness estimation is performed using cumbersome instrumentations (e.g. robots), and by approximating robot joint angles and torques to the human ones. This paper proposes a methodology and an experimental setup to measure wrist joint stiffness in unstructured environments, with the twofold aim of: 1) providing a geometric framework in order to derive angular displacements and torques at the wrist Flexion/Extension (FE) and Radial/Ulnar Deviation (RUD) axes of rotation, using a subject specific kinematic model; 2) suggesting an experimental setup made of two portable sensors for motion tracking and one load cell, to allow for measurements in out-of-the-lab scenarios. We tested our method on a hardware mockup of wrist kinematics, providing a ground truth for estimated angles and torques at FE and RUD joints. The experimental validation showed average absolute errors in FE and RUD angles of 0.005 rad and 0.0167 rad respectively, and an average error of FE and RUD torques of 0.006 Nm and 0.003 Nm.
用于估计人类手腕关节刚度的几何框架*
关节刚度的估计对于研究人体运动控制和神经系统疾病的临床评估至关重要。通常,刚度估计是使用笨重的仪器(例如机器人)进行的,并且通过将机器人关节的角度和扭矩近似于人类的角度和扭矩。本文提出了一种在非结构化环境中测量手腕关节刚度的方法和实验装置,其目的有两个:1)提供一个几何框架,以便使用受试者特定的运动学模型推导手腕屈伸(FE)和桡尺偏(RUD)旋转轴上的角位移和扭矩;2)提出了一种实验装置,由两个用于运动跟踪的便携式传感器和一个称重传感器组成,以便在实验室外的情况下进行测量。我们在手腕运动学的硬件模型上测试了我们的方法,为FE和RUD关节的估计角度和扭矩提供了一个基本的事实。实验验证表明,FE和RUD角的平均绝对误差分别为0.005 rad和0.0167 rad, FE和RUD扭矩的平均误差分别为0.006 Nm和0.003 Nm。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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