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运动速度与曲率之间幂律关系的起源:模拟肌肉力学和肢体动力学的影响。

Origins of the power law relation between movement velocity and curvature: modeling the effects of muscle mechanics and limb dynamics.

作者信息

Gribble P L, Ostry D J

机构信息

McGill University, Montreal, Quebec, Canada.

出版信息

J Neurophysiol. 1996 Nov;76(5):2853-60. doi: 10.1152/jn.1996.76.5.2853.

Abstract
  1. When subjects trace patterns such as ellipses, the instantaneous velocity of movements is related to the instantaneous curvature of the trajectories according to a power law-movements tend to slow down when curvature is high and speed up when curvature is low. It has been proposed that this relationship is centrally planned. 2. The arm's muscle properties and dynamics can significantly affect kinematics. Even under isometric conditions, muscle mechanical properties can affect the development of muscle forces and torques. Without a model that accounts for these effects, it is difficult to distinguish between kinematic patterns that are attributable to central control and patterns that arise because of dynamics and muscle properties and are not represented in the underlying control signals. 3. In this paper we address the nature of the control signals that underlie movements that obey the power law. We use a numerical simulation of arm movement control based on the lambda version of the equilibrium point hypothesis. We demonstrate that simulated elliptical and circular movements, and elliptical force trajectories generated under isometric conditions, obey the power law even though there was no relation between curvature and speed in the modeled control signals. 4. We suggest that limb dynamics and muscle mechanics-specifically, the springlike properties of muscles-can contribute significantly to the emergence of the power law relationship in kinematics. Thus, without a model that accounts for these effects, care must be taken when making inferences about the nature of neural control.
摘要
  1. 当受试者追踪诸如椭圆之类的图案时,运动的瞬时速度与轨迹的瞬时曲率根据幂律相关——当曲率高时运动往往会减慢,而当曲率低时运动则会加速。有人提出这种关系是由中枢计划的。2. 手臂的肌肉特性和动力学可以显著影响运动学。即使在等长条件下,肌肉的力学特性也会影响肌肉力量和扭矩的发展。如果没有一个考虑这些影响的模型,就很难区分归因于中枢控制的运动模式和由于动力学及肌肉特性而产生且未在潜在控制信号中体现的模式。3. 在本文中,我们探讨了遵循幂律的运动背后的控制信号的本质。我们基于平衡点假设的拉姆达版本对手臂运动控制进行了数值模拟。我们证明,模拟的椭圆和圆周运动,以及在等长条件下产生的椭圆力轨迹,即使在建模的控制信号中曲率和速度之间没有关系,也遵循幂律。4. 我们认为肢体动力学和肌肉力学——具体来说,肌肉的弹簧状特性——可以对运动学中幂律关系的出现做出重大贡献。因此,如果没有一个考虑这些影响的模型,在推断神经控制的本质时必须谨慎。

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