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Postural control of a musculoskeletal model against multidirectional support surface translations

机译:针对多向支撑表面平移的肌肉骨骼模型的姿势控制

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摘要

The human body is a complex system driven by hundreds of muscles, and its control mechanisms are not sufficiently understood. To understand the mechanisms of human postural control, neural controller models have been proposed by different research groups, including our feed-forward and feedback control model. However, these models have been evaluated under forward and backward perturbations, at most. Because a human body experiences perturbations from many different directions in daily life, neural controller models should be evaluated in response to multidirectional perturbations, including in the forward/backward, lateral, and diagonal directions. The objective of this study was to investigate the validity of an NC model with FF and FB control under multidirectional perturbations. We developed a musculoskeletal model with 70 muscles and 15 degrees of freedom of joints, positioned it in a standing posture by using the neural controller model, and translated its support surface in multiple directions as perturbations. We successfully determined the parameters of the neural controller model required to maintain the stance of the musculoskeletal model for each perturbation direction. The trends in muscle response magnitudes and the magnitude of passive ankle stiffness were consistent with the results of experimental studies. We conclude that the neural controller model can adapt to multidirectional perturbations by generating suitable muscle activations. We anticipate that the neural controller model could be applied to the study of the control mechanisms of patients with torso tilt and diagnosis of the change in control mechanisms from patients’ behaviors.
机译:人体是由数百个肌肉驱动的复杂系统,其控制机制尚未得到足够的了解。为了了解人体姿势控制的机制,不同研究小组提出了神经控制器模型,包括我们的前馈和反馈控制模型。但是,这些模型最多只能在正向和反向扰动下进行评估。由于人体在日常生活中会经历来自许多不同方向的扰动,因此应响应多方向扰动(包括向前/向后,横向和对角线方向)来评估神经控制器模型。这项研究的目的是调查多方向摄动下带有FF和FB控制的NC模型的有效性。我们开发了具有70条肌肉和15个关节自由度的肌肉骨骼模型,通过使用神经控制器模型将其定位为站立姿势,并在多个方向上将其支撑表面平移为扰动。我们成功地确定了神经控制器模型的参数,这些参数对于每个扰动方向都保持了肌肉骨骼模型的姿态。肌肉反应幅度和被动踝关节僵硬程度的趋势与实验研究的结果一致。我们得出的结论是,神经控制器模型可以通过生成合适的肌肉激活来适应多向扰动。我们预计,神经控制器模型可以用于研究躯干倾斜患者的控制机制,并根据患者的行为诊断控制机制的变化。

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