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一种用于模拟从坐姿到行走运动中补偿策略的平面神经肌肉控制器。

A planar neuromuscular controller to simulate compensation strategies in the sit-to-walk movement.

作者信息

van der Kruk Eline, Geijtenbeek Thomas

机构信息

Department of Biomechanical Engineering, Faculty of Mechanical Engineering (3me), Delft University of Technology, Delft, the Netherlands.

Goatstream, Utrecht, the Netherlands.

出版信息

PLoS One. 2024 Jun 13;19(6):e0305328. doi: 10.1371/journal.pone.0305328. eCollection 2024.

Abstract

Standing up from a chair is a key daily life activity that is sensitive to functional limitations as we age and associated with falls, frailty, and institutional living. Predictive neuromusculoskeletal models can potentially shed light on the interconnectivity and interdependency of age-related changes in neuromuscular capacity, reinforcement schemes, sensory integration, and adaptation strategies during stand-up. Most stand-up movements transfer directly into walking (sit-to-walk). The aim of this study was to develop and validate a neuromusculoskeletal model with reflex-based muscle control that enables simulation of the sit-to-walk movement under various conditions (seat height, foot placement). We developed a planar sit-to-walk musculoskeletal model (11 degrees-of-freedom, 20 muscles) and neuromuscular controller, consisting of a two-phase stand-up controller and a reflex-based gait controller. The stand-up controller contains generic neural pathways of delayed proprioceptive feedback from muscle length, force, velocity, and upper-body orientation (vestibular feedback) and includes both monosynaptic an antagonistic feedback pathways. The control parameters where optimized using a shooting-based optimization method, based on a high-level optimization criterium. Simulations were compared to recorded kinematics, ground reaction forces, and muscle activation. The simulated kinematics resemble the measured kinematics and muscle activations. The adaptation strategies that resulted from alterations in seat height, are comparable to those observed in adults. The simulation framework and model are publicly available and allow to study age-related compensation strategies, including reduced muscular capacity, reduced neural capacity, external perturbations, and altered movement objectives.

摘要

从椅子上站起来是一项关键的日常生活活动,随着年龄增长,它对功能限制很敏感,并且与跌倒、身体虚弱和机构生活相关。预测性神经肌肉骨骼模型可能有助于揭示在站立过程中,神经肌肉能力、强化方案、感觉整合和适应策略等与年龄相关变化的相互联系和相互依存关系。大多数站立动作会直接过渡到行走(从坐到走)。本研究的目的是开发并验证一个基于反射的肌肉控制神经肌肉骨骼模型,该模型能够模拟在各种条件下(座椅高度、脚部位置)的从坐到走动作。我们开发了一个平面的从坐到走肌肉骨骼模型(11个自由度,20块肌肉)和神经肌肉控制器,它由一个两阶段站立控制器和一个基于反射的步态控制器组成。站立控制器包含来自肌肉长度、力量、速度和上身方向(前庭反馈)的延迟本体感觉反馈的通用神经通路,并且包括单突触和拮抗反馈通路。基于一个高级优化标准,使用基于打靶的优化方法对控制参数进行了优化。将模拟结果与记录的运动学、地面反作用力和肌肉激活情况进行了比较。模拟的运动学与测量的运动学和肌肉激活情况相似。座椅高度改变所产生的适应策略与在成年人中观察到的策略相当。该模拟框架和模型已公开可用,可用于研究与年龄相关的补偿策略,包括肌肉能力下降、神经能力下降、外部扰动和改变的运动目标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3516/11175457/6e796e491c93/pone.0305328.g001.jpg

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