COMPUTATIONAL FRAMEWORK FOR SIMULATING JOINT MECHANICS

模拟关节力学的计算框架

基本信息

  • 批准号:
    6603899
  • 负责人:
  • 金额:
    $ 6.9万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2002
  • 资助国家:
    美国
  • 起止时间:
    2002-05-01 至 2005-04-30
  • 项目状态:
    已结题

项目摘要

Mechanical loading and especially dynamic loading, is believed to play a major role in degenerative joint diseases. Furthermore, motion (i.e., kinematics) and loading (i.e., contact stresses) often interact to influence disease progression. Thus, knowledge of in vivo joint motion and loading during functional activities would help address this clinically significant issue. While dynamic imaging advances now permit accurate measurement of in vivo joint kinematics, a non-invasive experimental approach does not exist for measuring in vivo joint loading. Consequently, computer simulations have been used to develop predictions given estimates of the muscle forces acting on the joint. However, current rigid body and deformable modeling approaches are not able to calculate contact stress results during movement in critical joints such as the knee. A logical solution to this problem is to incorporate deformable joint models into a larger rigid body dynamic model, thereby obtaining the advantages of both approaches. However, the computation cost of such a hybrid approach is currently a limiting factor. This project therefore proposes the development of a parallel-processing framework for studying human joint mechanics. The specific aims of the project are as follows: (1) Create a dynamic musculoskeletal model with deformable knee joint contact. Deformable contact in the knee will be studied initially since the knee is the most commonly injured joint. (2) Incorporate this model into a parallel-processing optimization framework. Parallel processing will be used to reduce the computational time for predictive optimizations from weeks to a matters of hours. (3) Evaluate the model's ability to predict experimental movement data. Pre-existing experimental movement data will be used to evaluate the model's ability to predict motion and ultimately joint contact stresses. The resulting functional virtual human model can then be used for basic research and clinical applications.
机械负荷,尤其是动态负荷,被认为在退行性关节疾病中发挥着重要作用。此外,运动(即运动学)和负载(即接触应力)通常相互作用以影响疾病进展。因此,了解功能活动期间的体内关节运动和负荷将有助于解决这个临床上重要的问题。虽然动态成像的进步现在允许精确测量体内关节运动学,但不存在用于测量体内关节负荷的非侵入性实验方法。因此,计算机模拟已被用来根据作用在关节上的肌肉力的估计来进行预测。然而,当前的刚体和可变形建模方法无法计算关键关节(例如膝盖)运动期间的接触应力结果。该问题的合理解决方案是将变形关节模型合并到更大的刚体动力学模型中,从而获得两种方法的优点。然而,这种混合方法的计算成本目前是一个限制因素。因此,该项目建议开发一个并行处理框架来研究人体关节力学。该项目的具体目标如下:(1)创建具有可变形膝关节接触的动态肌肉骨骼模型。由于膝盖是最常受伤的关节,因此首先将研究膝盖的变形接触。 (2)将该模型纳入并行处理优化框架中。并行处理将用于将预测优化的计算时间从几周缩短到几个小时。 (3) 评估模型预测实验运动数据的能力。预先存在的实验运动数据将用于评估模型预测运动和最终关节接触应力的能力。由此产生的功能虚拟人体模型可用于基础研究和临床应用。

项目成果

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BENJAMIN J FREGLY其他文献

BENJAMIN J FREGLY的其他文献

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{{ truncateString('BENJAMIN J FREGLY', 18)}}的其他基金

OpenSim Enhancements to Enable Computational Design of Personalized Treatments for Movement Impairments
OpenSim 增强功能可实现针对运动障碍的个性化治疗的计算设计
  • 批准号:
    10297893
  • 财政年份:
    2021
  • 资助金额:
    $ 6.9万
  • 项目类别:
OpenSim Enhancements to Enable Computational Design of Personalized Treatments for Movement Impairments
OpenSim 增强功能可实现针对运动障碍的个性化治疗的计算设计
  • 批准号:
    10482399
  • 财政年份:
    2021
  • 资助金额:
    $ 6.9万
  • 项目类别:
OpenSim Enhancements to Enable Computational Design of Personalized Treatments for Movement Impairments
OpenSim 增强功能可实现针对运动障碍的个性化治疗的计算设计
  • 批准号:
    10680443
  • 财政年份:
    2021
  • 资助金额:
    $ 6.9万
  • 项目类别:
Real-Time Model-Based Gait Retraining for Knee Osteoarthritis Rehabilitation
基于实时模型的膝骨关节炎康复步态再训练
  • 批准号:
    7305926
  • 财政年份:
    2007
  • 资助金额:
    $ 6.9万
  • 项目类别:
Real-Time Model-Based Gait Retraining for Knee Osteoarthritis Rehabilitation
基于实时模型的膝骨关节炎康复步态再训练
  • 批准号:
    7495645
  • 财政年份:
    2007
  • 资助金额:
    $ 6.9万
  • 项目类别:
COMPUTATIONAL FRAMEWORK FOR SIMULATING JOINT MECHANICS
模拟关节力学的计算框架
  • 批准号:
    6465453
  • 财政年份:
    2002
  • 资助金额:
    $ 6.9万
  • 项目类别:
COMPUTATIONAL FRAMEWORK FOR SIMULATING JOINT MECHANICS
模拟关节力学的计算框架
  • 批准号:
    6732078
  • 财政年份:
    2002
  • 资助金额:
    $ 6.9万
  • 项目类别:

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