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人体肌骨的多柔体系统动力学研究进展

郭建峤,王言冰,田强,任革学,胡海岩

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郭建峤, 王言冰, 田强, 任革学, 胡海岩. 人体肌骨的多柔体系统动力学研究进展. 力学进展, 2022, 52(2): 253-310 doi: 10.6052/1000-0992-21-056
引用本文: 郭建峤, 王言冰, 田强, 任革学, 胡海岩. 人体肌骨的多柔体系统动力学研究进展. 力学进展, 2022, 52(2): 253-310doi:10.6052/1000-0992-21-056
Guo J Q, Wang Y B, Tian Q, Ren G X, HU H Y. Advances in flexible multibody dynamics of human musculoskeletal systems. Advances in Mechanics, 2022, 52(2): 253-310 doi: 10.6052/1000-0992-21-056
Citation: Guo J Q, Wang Y B, Tian Q, Ren G X, HU H Y. Advances in flexible multibody dynamics of human musculoskeletal systems.AdvancesinMechanics, 2022, 52(2): 253-310doi:10.6052/1000-0992-21-056

人体肌骨的多柔体系统动力学研究进展

doi:10.6052/1000-0992-21-056
基金项目:国家自然科学基金青年基金(12102035), 中国博士后基金站前特别资助(2020TQ0042), 国家杰出青年科学基金(12125201). 感谢北京航空航天大学王丽珍教授、北京体育大学刘卉教授以及匿名评阅专家对本文提出的修改建议.
详细信息
    作者简介:

    郭建峤, 北京理工大学博士后, 助理研究员. 2015年6月毕业于同济大学工程力学专业, 获工学学士学位; 2020年6月毕业于清华大学动力学与控制专业, 获工学博士学位; 同年进入北京理工大学宇航学院力学系, 从事博士后研究,合作导师胡海岩院士. 主要从事运动生物力学与多体系统动力学的交叉研究, 主要包括: 人体肌肉与骨骼系统动力学建模, 神经肌骨系统生物材料黏弹性本构建立, 多柔体系统动力学建模与计算方法等. 作为第一作者/通信作者在《Proceedings of the Royal Society A》《Biomechanics and Modeling in Mechanobiology》《Nonlinear Dynamics, Multibody System Dynamics》等国际期刊发表多篇论文, 在首届“运动生物力学与体育科技促进研讨会”做特邀报告. 曾获得清华大学优秀博士论文, 上海市优秀毕业生等荣誉称号

    通讯作者:

    guojianqiao@bit.edu.cn

  • 中图分类号:O313.7

Advances in flexible multibody dynamics of human musculoskeletal systems

More Information
  • 摘要:人体肌肉骨骼系统简称肌骨系统, 包括骨骼、骨骼肌与关节连接, 其力学模型是典型的多柔体系统. 从多体动力学角度研究肌骨系统, 主要关注其在运动过程中的肌肉内力、关节力矩及产生的动力学影响, 属于动力学与生物力学的交叉融合. 肌骨系统的多体动力学模型已被广泛地应用于临床医学、竞技体育、军事训练、人机工程等诸多领域, 其仿真结果可为提高人体运动能力、降低关节载荷与能耗、避免运动损伤、加快康复进程等提供重要计算参考数据. 与此同时, 上述研究亦对肌骨动力学研究提出了许多新挑战. 本文综述了人体肌骨多柔体系统动力学相关研究进展, 包括骨骼肌功能解剖与生物力学建模、神经与肌肉控制理论、肌骨系统动力学问题与求解方法, 以及近年来肌骨多体动力学在步态分析、飞行员抗荷动作、口颌手术规划等领域的典型应用. 与工程领域的机械多体系统相比, 人体肌骨多体系统具有肌肉内力主动性与肌肉控制冗余性两大特征. 现有骨骼肌模型难以同时考虑肌肉的解剖结构、三维几何与肌力产生的生物化学机制. 已有大多数肌骨模型采用静态优化假设消除肌肉冗余性, 忽略了肌肉与肌腱内力平衡及兴奋收缩耦联机制. 此外, 目前仍缺乏实现肌骨模型个性化的无创在体测试手段. 未来, 人体肌骨多体动力学研究将会向更精确、智能、个性化的方向发展, 成为动力学与生物力学交叉的热点研究领域.

  • 图 1人体肌骨系统多体动力学模型. (a) OpenSim全人体模型(Raabe & Chaudhari 2016), (b) Anybody全人体模型(Bassani et al. 2017), (c) LifeMOD全人体模型(Kia et al. 2014), (d) ArtiSynth口颌模型(Stavness et al. 2011)

    图 2人体肌骨模型典型应用场景. (a) 人工髋关节假体设计(Zhang et al. 2015), (b) 脑瘫患儿关节僵硬缓解(Van Der Krogt et al. 2016), (c) 士兵负重步态(Xiang et al. 2009), (d) 汽车座椅减振(Zhang et al. 2019a)

    图 3骨骼肌多级结构(Gotti et al. 2020)

    图 4骨骼肌Hill-Zajac模型(Zajac 1989). (a) 对称双羽状肌模型(Guo J et al. 2020b), 包括主动收缩元、被动弹性元与串联弹性元; (b) 主动与被动肌力随肌纤维长度变化曲线(Silva & Ambrósio 2003,Guo J et al. 2020a)及其与趾长伸肌 (EDL, EDII) , 胫骨前肌 (TA) 实验比较(Gollapudi & Lin 2009,Winters et al. 2011); (c) 主动肌力随肌纤维收缩速度变化曲线及其与生理学实验(Joyce et al. 1969,Mashima 1984)比较; (d) 肌腱串联弹性元肌力随肌纤维长度变化曲线(Blankevoort et al. 1991)及其与生理学实验 (Magnusson et al. 2001,Maganaris & Paul 2002)比较

    图 5肌肉与骨骼缠绕描述. (a) 起止点简单连线及通过点约束(Suderman & Vasavada 2012), (b)简单几何体障碍设置(Suderman et al. 2012)

    图 6基于非负矩阵分解(Févotte & Idier 2011), 由健康人3个步态周期提取的典型肌肉协同模式

    图 7Walter等(2021)建立的多层级神经与运动控制模型.

    图 8多柔体动力学在肌骨系统建模中的应用. (a)基于浮动节点坐标描述建立的小变形股骨颈模型(Kłodowski et al. 2012), (b)柔性肱二头肌、肱三头肌模型(Gfrerer & Simeon 2021), (c)柔性膈肌模型(Guo J et al. 2021a)

    图 9基于非刚性迭代最近点方法(Amberg et al. 2007)映射肌肉附着点. (a) 基于Anybody标准口颌模型(de Zee et al. 2007)映射到患者, (b) 基于一名健康人肌肉附着区域, 映射到患者

    图 10足底接触力模型(Brown & McPhee 2018). (a)椭球接触模型, (b)实验与仿真足底压力结果比较

    图 11人体步态同步测量方法. (a)红外与视频混合动作捕捉系统, (b)视频AI-21点模型与红外标记点同步测量

    图 12腹腔多柔体动力学模型(Guo J et al. 2021a). (a)躯干隔离体受力分析, (b)柔性核心肌群模型, (c)腹内压气柱模型

    图 13结合生物力学测量与肌骨多体动力学仿真的口颌植入物设计. (a) 下颌骨运动及咀嚼肌EMG测量, (b) 患者术后口颌肌骨动力学模型

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