通过功能性关节定义和使用OpenSim实时模拟来预测神经肌肉训练的前进膝关节引时刻
Fabian Goell1,2, Bjoern Braunstein2,3,4,5, Maike Stemmler6
1Faculty of Medical Engineering and Technomathematics, Aachen University of Applied Sciences, Aachen, Germany.
PloS one
|June 10, 2025
概括
个性化的OpenSim模型在神经肌肉训练期间改善了膝盖引时刻估计. 功能性关节参数可以提高生物机械模拟的准确性,从而更好地治疗肌肉骨疾病和预防伤害.
科学领域:
- 生物力学 生物力学
- 肌肉骨系统的建模
- 神经肌肉训练是一种神经肌肉训练.
背景情况:
- 神经肌肉训练对于治疗肌肉骨疾病和预防与年龄相关的肌肉损失至关重要.
- 准确估计关节的时刻,如膝盖引时刻,对于有效的康复和性能分析至关重要.
- 当前的肌肉骨模型通常依赖于传统的缩放方法,这可能会限制个性化和准确性.
研究的目的:
- 评估 OpenSim 肌肉骨模型的不同个性化方法.
- 评估这些方法的实时实施,以估计在腿压练习期间的外部膝盖引力时刻.
- 将个性化模型的准确性与传统的缩放方法进行比较.
主要方法:
- 利用机器人神经肌肉训练平台进行同度和动态腿部伸展练习.
- 收集了来自13名受试者的3D运动捕捉和力板数据.
- 集成功能性关节参数,来自动态参考运动,进入OpenSim模型,以实现个性化关节表示.
- 将这种集成与传统的缩放方法进行比较.
主要成果:
- 功能性关节轴集成显著提高了生物力学模拟的准确性.
- 与传统缩放相比,个性化的OpenSim模型提供了更精确的实时估计外部膝关节引力时刻.
- 该研究表明了个性化模型参数在生物力学研究中的重要性.
结论:
- 个性化的OpenSim模型,结合功能性关节参数,在估计膝盖引矩时提供更高的准确性.
- 这些先进的建模技术对于神经肌肉训练和康复中精确的生物机械分析至关重要.
- 肌肉骨模型中的个性化是改善肌肉骨疾病治疗策略和提高性能的关键.
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