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.

我的研究重点是对人体步态模式的自然变异性或我们行走的方式的自然变异性发展，作为将因关节损伤或病理而导致正常情况发生变化的基础。我们的肌肉的协调使用，下肢（脚踝，膝盖，臀部）中关节的运动模式以及当我们在人之间自然行走时在整个关节中传播的力量。现在，我们拥有非常复杂的实验室的技术，使我们能够随着时间的流逝捕获和记录所有这些方面。这导致了一系列时间变化和相关的数据，旨在代表我们的单个步行模式。尽管有大量的应用研究报告在这些变量因受伤和疾病的变量中存在许多差异，但即使在健康个体中，对这些随时间变化的测量的关系仍然存在很差的了解，因此，了解可能有受伤或疾病风险的步行模式的有限能力。拟议的研究结合了复杂的生物力学和统计建模技术，以识别描述每个关节内部运动，力量和肌肉活动之间关系（髋关节，膝盖和脚踝）之间的关系的特征，并在我们的关节之间提供了更完整的描述下肢生物力学在步行过程中的描述。这项研究将探索健康步行力学与年龄相关的变化，并根据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伤害或疾病产生影响。在我们行走时我们的关节表面之间传播的力很难计算，但可以导致损伤和疾病的发展。这项研究还将探讨关节运动，肌肉使用和摘要力测量如何在步行过程中有助于联合力量，并提供更有效的方法来代表这些力量，以用于转化步态分析应用。拟议的研究将显着提高我们对步行模式中人与人之间的变异性的理解，以及这可能会导致步行过程中下肢关节机械环境的差异。了解用于描述大量健康人群中的步行模式的联合层次变量之间的关系将提供有关未受伤的，未解决的步行力学的重要知识，以及步态分析应用的规范基础。这项研究的结果将用于检查和理解从临床治疗和诊断，预防性肌肉骨骼健康计划以及行业/职业设计和评估等应用中的步行模式偏差。