Department of Kinesiology and Applied Physiology, University of Delaware, Newark, Delaware, United States of America.
Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
PLoS Comput Biol. 2024 Mar 18;20(3):e1011861. doi: 10.1371/journal.pcbi.1011861. eCollection 2024 Mar.
The walking human body is mechanically unstable. Loss of stability and falling is more likely in certain groups of people, such as older adults or people with neuromotor impairments, as well as in certain situations, such as when experiencing conflicting or distracting sensory inputs. Stability during walking is often characterized biomechanically, by measures based on body dynamics and the base of support. Neural control of upright stability, on the other hand, does not factor into commonly used stability measures. Here we analyze stability of human walking accounting for both biomechanics and neural control, using a modeling approach. We define a walking system as a combination of biomechanics, using the well known inverted pendulum model, and neural control, using a proportional-derivative controller for foot placement based on the state of the center of mass at midstance. We analyze this system formally and show that for any choice of system parameters there is always one periodic orbit. We then determine when this periodic orbit is stable, i.e. how the neural control gain values have to be chosen for stable walking. Following the formal analysis, we use this model to make predictions about neural control gains and compare these predictions with the literature and existing experimental data. The model predicts that control gains should increase with decreasing cadence. This finding appears in agreement with literature showing stronger effects of visual or vestibular manipulations at different walking speeds.
行走的人体在机械上是不稳定的。在某些人群中,如老年人或患有运动神经损伤的人,以及在某些情况下,如在遇到冲突或分散注意力的感觉输入时,更容易失去稳定性并摔倒。行走时的稳定性通常通过基于身体动力学和支撑基础的测量来生物力学特征来描述。另一方面,神经控制对直立稳定性的影响并没有纳入常用的稳定性测量中。在这里,我们使用建模方法来分析考虑生物力学和神经控制的人类行走稳定性。我们将行走系统定义为生物力学和神经控制的组合,使用著名的倒立摆模型来描述生物力学,使用基于质心在中间位置的状态的足部位置的比例-微分控制器来描述神经控制。我们对该系统进行了形式分析,并表明对于任何系统参数选择,总是存在一个周期性轨道。然后,我们确定这个周期性轨道是否稳定,即对于稳定的行走,神经控制增益值应该如何选择。在正式分析之后,我们使用该模型对神经控制增益进行预测,并将这些预测与文献和现有实验数据进行比较。该模型预测控制增益应随步速的降低而增加。这一发现似乎与文献一致,即表明在不同的行走速度下,视觉或前庭处理的影响更强。