Scalable Biomechanical Modeling of Joint and Muscle Forces in the Study of Knee Osteoarthritis

膝骨关节炎研究中关节和肌肉力的可扩展生物力学模型

• 批准号: RGPIN-2015-05106
• 负责人: AstephenWilson, Janie
• 金额: $ 1.82万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=644243
• 关键词: Scalable; Biomechanical; Modeling; Joint; Muscle

My research is focused on developing an improved understanding of the natural variability in human gait patterns, or the manner in which we walk, as a basis for which to compare changes from normal due to joint injury or pathology. The coordinated use of our muscles, the movement patterns of the joints in our lower limbs (ankles, knees, hips), and the forces that propagate throughout our joints as we walk vary naturally from person to person. We now have the technology for very sophisticated laboratories that allows us to capture and record all of these aspects over time as we walk. This results in a large set of time-varying and correlated data meant to represent our individual walking pattern. Despite a significant amount of applied research reporting many differences in these variables with injury and disease, there remains a poor understanding of the relationships among and within these time-varying measurements even in healthy individuals, and therefore a limited ability to understand walking patterns that might be at risk for injury or disease. The proposed research combines sophisticated biomechanical and statistical modeling techniques to identify features of healthy walking patterns that describe relationships between joint movement, forces and muscle activity within each joint (hip, knee and ankle), and between our joints to provide a more complete description of lower limb biomechanics during walking. The research will explore age-related changes in healthy walking mechanics, and natural groupings of individuals based on their walking mechanics, as different walking strategies may have implications for future injury or disease. The forces that propagate between the surfaces of our joints as we walk are difficult to calculate, but can contribute to injury and disease development. This research will also explore how joint movement, muscle use and summary force measurements contribute to joint forces during walking, and provide a more efficient method for representing these forces for use in translational gait analysis applications. The proposed research will significantly improve our understanding of the person-to-person variability in walking patterns, and how this may contribute to differences in the mechanical environment of lower limb joints during walking. Understanding the relationships between the joint-level variables used to describe walking patterns in a large healthy population will provide important knowledge of uninjured, non-diseased walking mechanics, and a normative basis for gait analysis applications. The outcome of this research will be used to examine and understand walking pattern deviations in applications ranging from clinical treatment and diagnosis, preventative musculoskeletal health initiatives, and industry/occupational design and assessments.

我的研究重点是提高对人类步态模式自然变异性的理解，或者我们走路的方式，作为比较关节损伤或病理导致的正常变化的基础。我们肌肉的协调使用，下肢关节（脚踝，膝盖，臀部）的运动模式，以及我们走路时通过关节传播的力量自然因人而异。我们现在拥有非常先进的实验室技术，使我们能够在行走时捕捉和记录所有这些方面。这导致了大量随时间变化且相关的数据，这些数据旨在代表我们的个人步行模式。尽管大量的应用研究报告了这些变量与损伤和疾病的许多差异，但即使在健康个体中，对这些随时间变化的测量之间和内部的关系仍然缺乏了解，因此理解可能存在损伤或疾病风险的步行模式的能力有限。拟议的研究结合了复杂的生物力学和统计建模技术，以确定健康步行模式的特征，这些特征描述了每个关节（髋关节，膝关节和踝关节）内关节运动，力量和肌肉活动之间的关系，以及我们的关节之间的关系，以提供行走过程中下肢生物力学的更完整描述。该研究将探讨健康步行力学中与年龄相关的变化，以及基于其步行力学的自然分组，因为不同的步行策略可能会对未来的损伤或疾病产生影响。当我们走路时，在我们关节表面之间传播的力很难计算，但可能会导致损伤和疾病的发展。这项研究还将探讨关节运动，肌肉使用和总结力测量如何在步行过程中有助于关节力，并提供一种更有效的方法来表示这些力用于平移步态分析应用程序。拟议的研究将显着提高我们对步行模式的人与人之间的差异的理解，以及这可能如何导致步行过程中下肢关节的力学环境差异。了解关节水平变量之间的关系，用于描述步行模式在一个大的健康人群将提供重要的知识，未受伤，非疾病的步行力学，步态分析应用程序的规范基础。这项研究的结果将被用来检查和了解步行模式偏差的应用范围从临床治疗和诊断，预防性肌肉骨骼健康举措，以及行业/职业设计和评估。