Dounskaia Natalia
Movement Control and Biomechanics Lab, Department of Kinesiology, Arizona State University, Tempe, AZ, 85287-0404, USA.
Biol Cybern. 2007 Feb;96(2):147-63. doi: 10.1007/s00422-006-0109-1. Epub 2006 Oct 10.
It has been observed that the motion of the arm end-point (the hand, fingertip or the tip of a pen) is characterized by a number of regularities (kinematic invariants). Trajectory is usually straight, and the velocity profile has a bell shape during point-to-point movements. During drawing movements, a two-thirds power law predicts the dependence of the end-point velocity on the trajectory curvature. Although various principles of movement organization have been discussed as possible origins of these kinematic invariants, the nature of these movement trajectory characteristics remains an open question. A kinematic model of cyclical arm movements derived in the present study analytically demonstrates that all three kinematic invariants can be predicted from a two-joint approximation of the kinematic structure of the arm and from sinusoidal joint motions. With this approach, explicit expressions for two kinematic invariants, the two-thirds power law during drawing movements and the velocity profile during point-to-point movements are obtained as functions of arm segment lengths and joint motion parameters. Additionally, less recognized kinematic invariants are also derived from the model. The obtained analytical expressions are further validated with experimental data. The high accuracy of the predictions confirms practical utility of the model, showing that the model is relevant to human performance over a wide range of movements. The results create a basis for the consolidation of various existing interpretations of kinematic invariants. In particular, optimal control is discussed as a plausible source of invariant characteristics of joint motions and movement trajectories.
人们已经观察到,手臂端点(手、指尖或笔尖)的运动具有许多规律性(运动学不变量)。轨迹通常是直线的,在点对点运动过程中速度分布呈钟形。在绘图运动中,三分之二次幂定律预测了端点速度与轨迹曲率的关系。尽管已经讨论了各种运动组织原则作为这些运动学不变量的可能起源,但这些运动轨迹特征的本质仍然是一个悬而未决的问题。本研究中推导的周期性手臂运动的运动学模型分析表明,所有这三个运动学不变量都可以从手臂运动学结构的双关节近似以及正弦关节运动中预测出来。通过这种方法,获得了两个运动学不变量的显式表达式,即绘图运动中的三分之二次幂定律和点对点运动中的速度分布,它们是手臂节段长度和关节运动参数的函数。此外,该模型还推导出了较少被认可的运动学不变量。所获得的解析表达式通过实验数据进一步验证。预测的高精度证实了该模型的实际效用,表明该模型在广泛的运动范围内与人类表现相关。这些结果为整合各种现有的运动学不变量解释奠定了基础。特别是,最优控制被讨论为关节运动和运动轨迹不变特征的一个合理来源。