脑瘫患者步态周期建模

Sabrina Otmani, G. Michon, B. Watier
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引用次数: 0

摘要

自主步态是运动障碍患者获得独立生活和避免去社会化的基本要素。在这种情况下,这项研究是EXOKID项目的一部分,该项目旨在为脑瘫儿童设计个性化的外骨骼。为了实现这种个性化,两个9岁的双胞胎姐妹,一个患有痉挛性脑瘫(C),一个健康(H),没有任何损伤,用肌电图(EMG)、运动学和力获取进行了几次散步。本文用力学微分方程建立了步行过程中膝关节和髋关节C的痉挛角位移模型。设计了两个模型:一个基于肌肉激活的时间,另一个使用遗传算法(GA)定义时间。这些模型强调了参与步行的肌肉的痉挛贡献(研究的关节激动剂和拮抗剂)及其激活。利用遗传算法对两种模型的激活幅值进行分析。两种模型的步态周期建模的决定系数(R2)均高于84%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Gait cycle modeling in cerebral palsy condition
Autonomous gait is a fundamental element for access to independent life and avoiding the de-socialization of people with motor disabilities. In this context, this research is part of the EXOKID project which aims at designing a personalized exoskeleton for children with cerebral palsy. For such personalisation, two 9 years old twin sisters, one with spastic cerebral palsy (C) and a healthy one (H) without any impairments, performed several walks with electromyography (EMG), kinematics and force acquisitions. This paper presents a model of the knee and hip's spastic angular displacement of C during a walk using mechanical differential equations. Two models were designed: one based on the timing of the muscular activation, the other where the timing is defined using a genetic algorithm (GA). These models highlight the spastic contributions of the muscles involved in the walk (agonists and antagonists of the joints studied) and their activations. The amplitude of the activations for both models was carried out using GA. Gait cycles were modeled with a determination coefficient (R2) higher than 84% for both models.
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