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维持姿势时的人体手部阻抗特性

Human hand impedance characteristics during maintained posture.

作者信息

Tsuji T, Morasso P G, Goto K, Ito K

机构信息

Faculty of Engineering, Hiroshima University, Japan.

出版信息

Biol Cybern. 1995;72(6):475-85. doi: 10.1007/BF00199890.

DOI:10.1007/BF00199890
PMID:7612720
Abstract

The present paper examines human hand impedance characteristics, including inertia and viscosity as well as stiffness, in multi-joint arm movements. While a subject maintains a given hand location, small external disturbances are applied to his hand by a manipulandum. The corresponding force-displacement vectors are measured and sampled over time in order to estimate the hand impedance by means of a second-order linear model. The experimental results in different subjects and hand locations are summarized as follows: (1) the estimated inertia matrices of the human hand well agrees with computed values using a two-joint arm model, (2) spatial variations of the stiffness ellipses are consistent with the experimental results of Mussa-Ivaldi et al. (1985), (3) hand stiffness and viscosity increase with the grip force of the subject, and (4) viscosity and stiffness ellipses tend to have similar orientation. The accuracy of the impedance estimation method is validated with a mechanical spring-mass system with known parameters.

摘要

本文研究了多关节手臂运动中人体手部的阻抗特性,包括惯性、粘性以及刚度。当受试者保持手部处于给定位置时,一个操作器会对手部施加小的外部干扰。测量并随时间采样相应的力 - 位移向量,以便通过二阶线性模型估计手部阻抗。不同受试者和手部位置的实验结果总结如下:(1)人体手部的估计惯性矩阵与使用双关节手臂模型计算的值非常吻合;(2)刚度椭圆的空间变化与穆萨 - 伊瓦尔迪等人(1985年)的实验结果一致;(3)手部刚度和粘性随受试者握力增加;(4)粘性和刚度椭圆往往具有相似的方向。通过具有已知参数的机械弹簧 - 质量系统验证了阻抗估计方法的准确性。

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本文引用的文献

1
Dependence of elbow viscoelastic behavior on speed and loading in voluntary movements.肘关节粘弹性行为在随意运动中对速度和负荷的依赖性。
Exp Brain Res. 1993;93(1):177-80. doi: 10.1007/BF00227793.
2
Virtual trajectory and stiffness ellipse during multijoint arm movement predicted by neural inverse models.神经逆模型预测的多关节手臂运动过程中的虚拟轨迹和刚度椭圆
Biol Cybern. 1993;69(5-6):353-62.
3
The mechanical behavior of the human forearm in response to transient perturbations.人类前臂对瞬态扰动的力学行为。
PLoS One. 2022 Nov 10;17(11):e0276980. doi: 10.1371/journal.pone.0276980. eCollection 2022.
4
Humans modulate arm stiffness to facilitate motor communication during overground physical human-robot interaction.人类调节手臂刚度,以在地面物理人机交互过程中促进运动交流。
Sci Rep. 2022 Nov 5;12(1):18767. doi: 10.1038/s41598-022-23496-z.
5
Leveraging Joint Mechanics Simplifies the Neural Control of Movement.利用关节力学简化运动的神经控制。
Front Integr Neurosci. 2022 Mar 21;16:802608. doi: 10.3389/fnint.2022.802608. eCollection 2022.
6
Evaluating Viscoelastic Properties of the Wrist Joint During External Perturbations: Influence of Velocity, Grip, and Handedness.评估外部扰动下腕关节的粘弹性特性:速度、握力和利手的影响。
Front Hum Neurosci. 2021 Oct 4;15:726841. doi: 10.3389/fnhum.2021.726841. eCollection 2021.
7
Simulation Evaluation for Methods Used to Determine Muscular Internal Force Based on Joint Stiffness Using Muscular Internal Force Feedforward Controller for Musculoskeletal System.基于肌肉骨骼系统肌肉内力前馈控制器,利用关节刚度确定肌肉内力的方法的仿真评估
Front Robot AI. 2021 Sep 27;8:699792. doi: 10.3389/frobt.2021.699792. eCollection 2021.
8
Variable Admittance Control Based on Human-Robot Collaboration Observer Using Frequency Analysis for Sensitive and Safe Interaction.基于人机协作观测器的变导纳控制的频率分析用于敏感和安全交互
Sensors (Basel). 2021 Mar 8;21(5):1899. doi: 10.3390/s21051899.
9
Behavioral and physiological correlates of kinetically tracking a chaotic target.跟踪动态混沌目标的行为和生理相关性。
PLoS One. 2020 Sep 18;15(9):e0239471. doi: 10.1371/journal.pone.0239471. eCollection 2020.
10
Estimation of Involuntary Components of Human Arm Impedance in Multi-Joint Movements via Feedback Jerk Isolation.通过反馈加加速度隔离估计多关节运动中人体手臂阻抗的非自主成分
Front Neurosci. 2020 May 25;14:459. doi: 10.3389/fnins.2020.00459. eCollection 2020.
Biol Cybern. 1982;44(1):35-46. doi: 10.1007/BF00353954.
4
The mechanical behavior of active human skeletal muscle in small oscillations.活跃人体骨骼肌在小振幅振荡中的力学行为。
J Biomech. 1982;15(2):111-21. doi: 10.1016/0021-9290(82)90043-4.
5
An organizing principle for a class of voluntary movements.一类自主运动的组织原则。
J Neurosci. 1984 Nov;4(11):2745-54. doi: 10.1523/JNEUROSCI.04-11-02745.1984.
6
Posture control and trajectory formation during arm movement.手臂运动过程中的姿势控制与轨迹形成。
J Neurosci. 1984 Nov;4(11):2738-44. doi: 10.1523/JNEUROSCI.04-11-02738.1984.
7
Neural, mechanical, and geometric factors subserving arm posture in humans.维持人类手臂姿势的神经、机械和几何因素。
J Neurosci. 1985 Oct;5(10):2732-43. doi: 10.1523/JNEUROSCI.05-10-02732.1985.
8
The coordination of arm movements: an experimentally confirmed mathematical model.手臂运动的协调:一个经实验验证的数学模型。
J Neurosci. 1985 Jul;5(7):1688-703. doi: 10.1523/JNEUROSCI.05-07-01688.1985.
9
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J Biomech. 1986;19(3):231-8. doi: 10.1016/0021-9290(86)90155-7.
10
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Biol Cybern. 1987;57(4-5):257-74. doi: 10.1007/BF00338819.