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静态多指抓握中的力与扭矩产生:生物力学与控制。II. 控制

Force and torque production in static multifinger prehension: biomechanics and control. II. Control.

作者信息

Zatsiorsky Vladimir M, Gregory Robert W, Latash Mark L

机构信息

Department of Kinesiology, The Pennsylvania State University, University Park, PA 16802, USA.

出版信息

Biol Cybern. 2002 Jul;87(1):40-9. doi: 10.1007/s00422-002-0320-7.

Abstract

The coordination of digits during combined force/torque production tasks was further studied using the data presented in the companion paper [Zatsiorsky et al. Biol Cybern this issue, Part I]. Optimization was performed using as criteria the cubic norms of (a) finger forces, (b) finger forces normalized with respect to the maximal forces measured in single-finger tasks, (c) finger forces normalized with respect to the maximal forces measured in a four-finger task, and (d) finger forces normalized with respect to the maximal moments that can be generated by the fingers. All four criteria failed to predict antagonist finger moments when these moments were not imposed by the task mechanics. Reconstruction of neural commands: The vector of neural commands c was reconstructed from the equation c=W(-1)F, where W is the finger interconnection weight matrix and F is the vector of finger forces. The neural commands ranged from zero (no voluntary force production) to one (maximal voluntary contraction). For fingers producing moments counteracting the external torque ('agonist' fingers), the intensity of the neural commands was well correlated with the relative finger forces normalized to the maximal forces in a four-finger task. When fingers produced moments in the direction of the external torque ('antagonist' fingers), the relative finger forces were always larger than those expected from the intensity of the corresponding neural commands. The individual finger forces were decomposed into forces due to 'direct' commands and forces induced by enslaving effects. Optimization of the neural commands resulted in the best correspondence between actual and predicted finger forces. The antagonist moments are, at least in part, due to enslaving effects: strong commands to agonist fingers also activated antagonist fingers.

摘要

在联合力/扭矩产生任务中,利用配套论文[扎齐奥尔斯基等人,《生物控制论》本期,第一部分]中呈现的数据,对指的协调性进行了进一步研究。优化过程采用以下标准:(a)手指力的立方范数;(b)相对于单指任务中测得的最大力进行归一化的手指力;(c)相对于四指任务中测得的最大力进行归一化的手指力;以及(d)相对于手指可产生的最大力矩进行归一化的手指力。当这些力矩不是由任务力学施加时,所有这四个标准都未能预测拮抗手指力矩。神经指令的重构:神经指令向量c由方程c = W(-1)F重构,其中W是手指互连权重矩阵,F是手指力向量。神经指令范围从零(无自主力产生)到一(最大自主收缩)。对于产生与外部扭矩相反力矩的手指(“主动肌”手指),神经指令的强度与相对于四指任务中最大力归一化的相对手指力密切相关。当手指产生与外部扭矩方向相同的力矩时(“拮抗肌”手指),相对手指力总是大于根据相应神经指令强度预期的值。各个手指力被分解为由于“直接”指令产生的力和由从属效应诱导产生的力。神经指令的优化导致实际手指力与预测手指力之间的最佳对应。拮抗力矩至少部分是由于从属效应:对主动肌手指的强烈指令也会激活拮抗肌手指。

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