Quantifying and Predicting Biomechanical Variability in Musculoskeletal Movement

量化和预测肌肉骨骼运动的生物力学变异性

• 批准号: RGPIN-2020-07172
• 负责人: Hurley, Jaclyn
• 金额: $ 1.68万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=741640
• 关键词: Quantifying; Predicting; Biomechanical; Variability; Musculoskeletal

Muscle and joint anatomy, and upper limb movement are highly diverse across the population. This diversity poses scientific challenges for understanding fundamental patterns of human movement. Establishing features of normal movement enables assessment of adaptations to these patterns from factors related to activities of daily living, work or recreation. The shoulder is complex, with several muscles and joints providing exceptional functional capabilities. However, the challenges described are amplified by this large movement range and postural flexibility. My research is dedicated to understanding fundamental upper limb movement across a diverse population, through studying tissue responses and adaptations to different mechanical factors and developing techniques to capture population variability. The integration of experimental and computer simulation methodologies will be used to address research objectives within three interrelated themes. 1) Variability in muscle coordination and movement in response to mechanical exposures. Modifiers of muscle control and movement will be investigated. This will include quantifying modifications in muscle coordination in response to mechanical exposures such as posture, force, and repetitive activity. Focus will be directed towards studying variability in muscle and joint strategies related to muscle fatigue and recovery, and the implications on musculoskeletal movement and function. These relationships will be investigated while considering variability across an anthropometrically diverse population. 2) Methodological advancement in the measurement of biological tissues. Research dedicated to refining and developing novel methodologies to non-invasively quantify biological tissues will be conducted. Specifically, the capabilities of ultrasound to measure key muscle and joint characteristics accurately will be studied. 3) Computer simulation of upper limb movement to predict differences in muscle control. Three-dimensional computer simulation enables the quantification and prediction of outcomes that may not be possible to measure experimentally. Computer models of human movement will be developed to study how variation in muscle control modifies complex movement patterns, notably through simulating a fatiguing muscular response. Anticipated outcomes from this research program will yield exciting, novel contributions to the natural sciences and engineering landscape in Canada. Innovative advancements pertaining to the control, coordination and adaptation of muscular strategies and their implications on upper limb movement will be ascertained. The fundamental discoveries of my research program will have important implications for optimizing human performance, preventing muscle and joint damage, and designing safe workplaces. These findings and the pertinent applications will have high relevance for our younger and aging highly diverse Canadian population.

肌肉和关节解剖结构以及上肢运动在整个人群中高度多样。这种多样性为理解人类运动的基本模式带来了科学挑战。建立正常运动的特征可以评估适应这些模式，从与日常生活，工作或娱乐活动有关的因素。肩膀很复杂，几种肌肉和关节具有出色的功能能力。但是，所描述的挑战被这个较大的运动范围和姿势灵活性所扩大。我的研究致力于通过研究组织反应和对不同机械因素的适应和开发捕获人群变异性的技术来理解各种各样人群的基本上肢运动。实验和计算机模拟方法的集成将用于解决三个相互关联的主题内的研究目标。 1）肌肉协调和运动响应机械暴露的变异性。将研究肌肉控制和运动的修饰符。这将包括响应诸如姿势，力和重复活性等机械暴露的响应，量化肌肉协调的修饰。重点将针对研究与肌肉疲劳和恢复有关的肌肉和关节策略的变异性，以及对肌肉骨骼运动和功能的影响。这些关系将在考虑拟人化多样的人群中的变异性时进行研究。 2）测量生物组织的方法学进步。将进行专门针对非侵入性量化生物组织的新方法的研究。具体而言，将精确研究超声测量关键肌肉和关节特征的能力。 3）上肢运动的计算机模拟，以预测肌肉控制的差异。三维计算机仿真可以定量和预测结果，这些结果可能无法通过实验进行测量。将开发人类运动的计算机模型来研究肌肉控制的变异如何改变复杂运动模式，特别是通过模拟疲劳的肌肉反应。该研究计划的预期结果将为加拿大的自然科学和工程景观提供令人兴奋的新颖贡献。将确定与肌肉策略的控制，协调和适应有关的创新进步及其对上肢运动的影响。我的研究计划的基本发现将对优化人类绩效，防止肌肉和关节损害以及设计安全的工作场所具有重要意义。这些发现和相关的应用将对我们年轻和老化的高度多样化的加拿大人口具有很高的相关性。