同时基于模型的关节,肌肉和肌硬度估计对肌强力-张力关系高度敏感
IEEE transactions on bio-medical engineering
|October 13, 2023
概括
这项研究引入了一种新的电肌图驱动的肌肉骨模型,以非侵入性地估计关节,肌肉和肌的刚性. 研究结果表明,目前的肌模型过于硬,需要重新校准才能进行准确的生物力学分析.
科学领域:
- 生物力学 生物力学
- 肌肉骨系统的建模
- 人类生理学 人类生理学
背景情况:
- 在活体中估计关节,肌肉和肌水平的性是具有挑战性的.
- 电肌图 (EMG) 驱动的模型估计了关节刚性,但缺乏多层次验证.
- 以前的验证由于没有同时在体内测量肌肉和肌硬度而受到限制.
研究的目的:
- 提出一种基于EMG的新型模型,可以在没有外部干扰或超声波的情况下估计多层硬度.
- 开发封闭式方程,以对肌肉骨参数进行个体特定的调整.
- 将模型与基于扰动的新型实验技术进行验证.
主要方法:
- 利用基于扰动的实验技术与动力测量和超声波用于参考刚度.
- 开发了一种新的EMG驱动的肌肉骨建模方法.
- 衍生出个人特有的肌肉骨参数,包括被动力-长度关系.
主要成果:
- 校准的EMG驱动模型估计参考数据的RMSE约为20%.
- 精确的多级硬度估计要求校准是比典型模型更符合标准的4倍.
- 确定在肌肉骨建模中常用的肌模型过于硬.
结论:
- 用EMG驱动的肌肉骨模型,当与广泛的参考数据校准时,产生现实的生物力学变量.
- 当前肌肉骨建模中的肌模型往往过于硬.
- 校准模型可以提高超出传感器限制的生物力学变量.
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