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运动生物力学发展现状及挑战

刘程林 郝卫亚 霍波

刘程林, 郝卫亚, 霍波. 运动生物力学发展现状及挑战. 力学进展, 待出版 doi: 10.6052/1000-0992-22-030
引用本文: 刘程林, 郝卫亚, 霍波. 运动生物力学发展现状及挑战. 力学进展, 待出版 doi: 10.6052/1000-0992-22-030
Liu C L, Hao W Y, Huo B. Advances and challenges in sports biomechanics. Advances in Mechanics, in press doi: 10.6052/1000-0992-22-030
Citation: Liu C L, Hao W Y, Huo B. Advances and challenges in sports biomechanics. Advances in Mechanics, in press doi: 10.6052/1000-0992-22-030

运动生物力学发展现状及挑战

doi: 10.6052/1000-0992-22-030
基金项目: 国家自然科学基金青年 (12102277) , 科技部重点研发计划“科技冬奥”专项, “国家科学化训练基地建设关键技术研究与示范”项目 (2018YFF0300800)资助. 感谢北京体育大学刘卉教授以及北京理工大学郭建峤博士对本文提出的修改建议.
详细信息
    作者简介:

    刘程林,博士,首都体育学院体育人工智能研究院副教授、硕士生导师。主持国家自然基金2项、北京市教委科技一般项目1项、国家体育总局科技助力项目1项,并参与国家重点研发计划项目、装备发展部预研项目、装备发展部快速转化项目、中央军委基础加强计划重点基础研究项目等多项课题研究工作。研究方向主要包括:运动疲劳对于神经肌肉协同控制的影响,疲劳状态下关节、肌肉损伤预测和分析,基于深度学习的人体姿态识别及其在运动技战术分析中的应用等。在《Biophysical Journal》等杂志发表SCI收录论文10余篇

    霍波, 博士, 教授, 博士生导师, 体育人工智能研究院院长, 运动生物力学研究中心首席专家. 作为项目负责人主持了科技部重点研发计划项目、国家自然科学基金项目多项. 2021年被体育总局评为“中国冰雪科学家”, 获得第六届中国创新挑战赛暨中关村第五届新兴领域专题赛优胜奖, 并指导学生获得省部级创新创业竞赛奖多项. 主要从事生物力学研究, 发现动态外力调控骨骼结构的新的细胞力学机制, 并研发了以骨骼肌肉动力学为核心的智能测试分析系统, 成功应用于多支国家队的北京冬奥备战训练, 助力相关运动员获得1金1银1铜的优异成绩. 发表杂志论文80余篇, 其中SCI收录论文50余篇. 出版学术专著1部、学科史1部, 参编专著7部 (章节) , 获批工信部规划教材1部

    通讯作者:

    liuchenglin@cupes.edu.cn

    huobo@cupes.edu.cn

  • 中图分类号: (O313)

Advances and challenges in sports biomechanics

More Information
  • 摘要: 狭义的运动生物力学特指人体运动中的生物力学, 主要解决竞技体育领域中如何提高运动成绩和减少运动损伤的问题. 随着相关学科的融合和发展, 当前运动生物力学的研究已扩展到与人类运动相关的生物学、医学、力学等学科领域. 近年来, 智能测试、大数据分析、人工智能等技术的快速发展, 对运动生物力学实验、仿真方法产生了重要的影响, 在不断拓展和深化着该学科的研究内容和方向的同时, 也对运动生物力学发展提出了新的挑战. 本文综述了近年来运动生物力学领域的研究现状, 并指出了相关研究方向的关键问题及发展趋势: 在理论建模和模拟仿真计算方面, 肌肉本构理论及肌肉力计算准确性是重点和难点; 实验测试的新技术在竞技体育运动项目中的应用研究中扮演重要角色, 其中基于深度学习的人体关键点检测算法在解决竞技体育的非接触测量方面有突破性进展; 对于骨、韧带、软骨、肌肉等组织的宏观损伤机制认识不断清晰, 但对于其早期损伤预测以及跨尺度损伤发生机制的研究仍有待深入; 智能可穿戴装备、人工智能等新技术开始应用于运动生物力学研究及实践, 成为目前运动生物力学领域最具活力的研究方向之一. 本文的综述表明当前运动生物力学研究越来越向智能化、个体化、定量化发展, 并正在与相关学科不断交叉融合, 持续推进着体育、健康、医疗等领域的科技创新发展.

     

  • 图  1  典型的膝关节双刚体模型(Richard et al. 2016). (a) 膝关节模型的坐标系统Qi: 小腿 (i = 2) , 大腿 (i = 3) 以及膝关节; (b) 从上到下表示四种不同的膝关节模型: 无关节模型 (N) 、球形模型 (S) 、并联机构 (P) 和刚度矩阵 (M)

    图  2  基于人体运动分析的多体动力学模型. (a) 平面多刚体力学建模(King et al. 2019); (b) Anybody全人体肌骨模型 (AnyBody Technology Inc., Denmark) ; (c) OpenSim全人体模型(Raabe and Chaudhari 2016)

    图  3  基于Hill-Zajac假设的肌肉收缩力模型. (a) Hill-Zajac模型的基本假设及力学模型的抽象过程(Zajac 1989); (b) 肌腱力随肌腱长度变化关系的实验(Magnusson et al. 2001, Maganaris and Paul 2002)和模型结果(Blankevoort et al. 1991); (c) 肌肉力与肌纤维长度关系的实验(Gollapud and Lin 2009, Winters et al. 2011)和模型结果(Arnold et al. 2010); (d) 肌肉力与肌纤维收缩速度关系的实验(Joyce et al. 1969, MASHIMA 1984)和模型结果(Blankevoort et al. 1991)

    图  4  肌骨动力学模拟在实践中的应用. (a) 不同步态的关节受力分析(Lerner et al. 2015), 局部放大图显示膝关节模型结构, 右侧逻辑图显示模型结构间位置和运动关系; (b) 人工关节评估和优化(Chen et al. 2014); (c) 人机耦合外骨骼助力装备的设计, 从左至右分别为外骨骼装置照片、人-机耦合骨骼肌肉动力学分析和实验照片(Gordon et al. 2018); (d) 专项运动技术动作优化和损伤分析(Trasolini et al. 2022)

    图  5  动力学参数测量设备. (a) 足底压力鞋垫在大跳台训练中的应用; (b) 三维测力台在下肢评估中的应用; (c) 分布式足底压力测试系统 (Materialise Inc., Belgium) ; (d) 等速肌力测试系统

    图  6  冬季项目训练智能管理系统(霍波等2022a). 结合生理学、运动学、动力学等参数的检测实现对人体心肺系统、骨骼肌肉系统建模分析, 实现多维度、精细化、科学化的运动训练管理

    图  7  短跑的起跑过程中关键动作和对应时间(Bezodis et al. 2019b).

    图  8  膝关节在体建模和有限元分析流程(Jogi et al. 2021). (a) 人体膝关节核磁共振成像图 (单层) ; (b) 对核磁图像进行不同组织的分割并用Mimics创建三维几何体; (c) ANSYS对三维模型划分网格; (d) 针对不同软组织刚度取值, 有限元模型计算得到每位受试者的胫骨关节变形结果

    图  9  三维人体姿态公开数据集. (a) Human3.6M人体姿态数据采集方案和采集过程; (b) HumanEVA数据集采集过程; (c) MPI-INF-3DHP数据采集过程

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