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.

我的研究重点是更好地理解人类步态模式的自然变异或我们行走的方式，作为比较由于关节损伤或病理导致的正常变化的基础。肌肉的协调使用、下肢关节（脚踝、膝盖、臀部）的运动模式以及行走时在关节中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，使我们能够在行走过程中捕捉并记录所有这些方面。这会产生大量随时间变化且相关的数据，旨在代表我们个人的行走模式。尽管大量的应用研究报告了这些变量与伤害和疾病之间的许多差异，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知之甚少，因此了解可能面临伤害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（臀部、膝盖和脚踝）内以及关节之间的关节运动、力和肌肉活动之间的关系，以提供步行过程中下肢生物力学的更完整的描述。该研究将探索健康步行力学与年龄相关的变化，以及基于步行力学的个体自然分组，因为不同的步行策略可能对未来的伤害或疾病产生影响。当我们行走时，在关节表面之间传播的力很难计算，但可能会导致伤害和疾病的发展。这项研究还将探索关节运动、肌肉使用和总结力测量如何影响步行过程中的关节力，并提供一种更有效的方法来表示这些力，以用于平移步态分析应用。拟议的研究将显着提高我们对步行模式的人与人差异的理解，以及这如何导致步行期间下肢关节机械环境的差异。了解用于描述大量健康人群步行模式的关节级变量之间的关系将为未受伤、无疾病的步行力学提供重要的知识，并为步态分析应用提供规范基础。这项研究的结果将用于检查和理解临床治疗和诊断、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。