Chang C C, Brown D R, Bloswick D S, Hsiang S M
Liberty Mutual Research Center for Safety and Health, 71 Frankland Road, Hopkinton, MA 01748, USA.
J Biomech. 2001 Apr;34(4):527-32. doi: 10.1016/s0021-9290(00)00222-0.
Previous optimization techniques for the prediction of lifting motion patterns often require a change in either the number of variables or the order of the mathematical functions used to express the angular displacement of selected joints in response to change in variant conditions. The resolution of predicted results can also be seriously constrained by the number of variables used. These restrictions may often limit the applicability of these methodologies. In this paper, we proposed a new methodology for generating the optimum motion patterns for para-sagittal lifting tasks. A detailed description of this methodology is introduced. An example of an analysis using this methodology is presented. The computer program generated lifting motion patterns with a reduction of the overall objective function values. The actual versus predicted lifting motion patterns are compared. Using this method, constraints can be added anywhere within the lifting cycle without the need of rewriting the whole program. These features provide for a more flexible and efficient prediction of the lifting motion.
先前用于预测提升运动模式的优化技术通常需要改变变量的数量或用于表达所选关节角位移以响应变化条件的数学函数的阶数。预测结果的分辨率也可能受到所用变量数量的严重限制。这些限制常常可能会限制这些方法的适用性。在本文中，我们提出了一种用于生成矢状旁提升任务最佳运动模式的新方法。介绍了该方法的详细描述。给出了使用该方法进行分析的一个示例。计算机程序生成了具有降低的总体目标函数值的提升运动模式。比较了实际与预测的提升运动模式。使用此方法，可以在提升周期内的任何位置添加约束，而无需重写整个程序。这些特性为提升运动提供了更灵活高效的预测。
