Taga G
Department of Pure and Applied Sciences, University of Tokyo, Japan.
Biol Cybern. 1995 Jul;73(2):113-21. doi: 10.1007/BF00204049.
Adaptive gaits of humans were produced as a result of emergent properties of a model based on the neurophysiology of the central pattern generator and the biomechanics of the human musculoskeletal system. We previously proposed a neuromusculoskeletal model for human locomotion, in which movements emerged as a stable limit cycle that was generated through the global entrainment among the neural system, composed of neural oscillators, the musculoskeletal system, and the environment. In the present study, we investigated the adaptability of this model under various types of environmental and task constraints. Using a computer simulation, it was found that walking movements were robust against mechanical perturbations, loads with a mass, and uneven terrain. Moreover, the speed of walking could be controlled by a single parameter which tonically drove the neural oscillators, and the step cycle could be entrained by a rhythmic input to the neural oscillators.
人类的适应性步态是基于中枢模式发生器的神经生理学和人类肌肉骨骼系统的生物力学构建的模型所产生的涌现特性的结果。我们之前提出了一个用于人类运动的神经肌肉骨骼模型，其中运动作为一个稳定的极限环出现，该极限环是通过由神经振荡器组成的神经系统、肌肉骨骼系统和环境之间的全局同步产生的。在本研究中，我们研究了该模型在各种类型的环境和任务约束下的适应性。通过计算机模拟发现，步行运动对机械扰动、负重和不平坦地形具有鲁棒性。此外，步行速度可以通过一个持续驱动神经振荡器的单一参数来控制，并且步周期可以通过对神经振荡器的节律性输入来同步。
