From template to anchors: transfer of virtual pendulum posture control balance template to adaptive neuromuscular gait model increases walking stability
From template to anchors: transfer of virtual pendulum posture control balance template to adaptive neuromuscular gait model increases walking stability
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DOI：
10.1098/rsos.181911
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发表时间：
2019-03-01
影响因子：
3.5
通讯作者：
Sharbafi, Maziar A.
中科院分区：
文献类型：
--
作者：
Davoodi, Ayoob;Mohseni, Omid;Sharbafi, Maziar A.
不同复杂程度的生物力学模型有助于理解腿部运动的基本原理。遵循基于模板和锚概念的逐步增加模型复杂性的最小方法，将弹簧负载倒立摆步行模型扩展为刚性躯干、臀部肌肉和反射控制，称为神经肌力调节顺应性髋关节模型。我们的控制策略包括腿力反馈来激活臀部肌肉(源于FMCH方法)，以及一个离散的线性二次型调节器来适应肌肉反射。NMF模型展示了类似人类行走的运动学和动力学特征，如继承自FMCH模型的虚拟摆(VP)概念。此外，NMF模型对姿态摄动的鲁棒性是FMCH模型的两倍，在自适应NMF模型中甚至进一步增强。这是由于内在的肌肉动力和反射增益的调整。在此基础上，我们首次展示了机械模板模型(例如VP概念)到更生理水平(NMF模型)的演变。这表明该模板模型可以成功地用于设计和控制具有更真实系统行为的鲁棒运动系统。
Biomechanical models with different levels of complexity are of advantage to understand the underlying principles of legged locomotion. Following a minimalistic approach of gradually increasing model complexity based on Template & Anchor concept, in this paper, a spring-loaded inverted pendulum-based walking model is extended by a rigid trunk, hip muscles and reflex control, called nmF (neuromuscular force modulated compliant hip) model. Our control strategy includes leg force feedback to activate hip muscles (originated from the FMCH approach), and a discrete linear quadratic regulator for adapting muscle reflexes. The nmF model demonstrates human-like walking kinematic and dynamic features such as the virtual pendulum (VP) concept, inherited from the FMCH model. Moreover, the robustness against postural perturbations is two times higher in the nmF model compared to the FMCH model and even further increased in the adaptive nmF model. This is due to the intrinsic muscle dynamics and the tuning of the reflex gains. With this, we demonstrate, for the first time, the evolution of mechanical template models (e.g. VP concept) to a more physiological level (nmF model). This shows that the template model can be successfully used to design and control robust locomotor systems with more realistic system behaviours.