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，以及上肢运动在整个人群中都是非常不同的。这种多样性对理解人类运动的基本模式提出了科学挑战。建立正常运动的特征可以从与日常生活、工作或娱乐活动相关的因素来评估对这些模式的适应。肩部很复杂，有几块肌肉和关节提供了非凡的功能。然而，这种大的运动范围和姿势灵活性放大了所描述的挑战。我的研究致力于通过研究组织对不同机械因素的反应和适应，以及开发捕捉种群变异性的技术，来了解不同人群中的基本上肢运动。将采用实验和计算机模拟方法相结合的方法，在三个相互关联的主题中处理研究目标。1)对机械暴露的肌肉协调和运动的可变性。将研究肌肉控制和运动的改良剂。这将包括量化肌肉协调性的变化，以响应机械暴露，如姿势、力量和重复活动。重点将集中在研究与肌肉疲劳和恢复有关的肌肉和关节策略的可变性，以及对肌肉骨骼运动和功能的影响。这些关系将被调查，同时考虑到人体测量不同的人群的可变性。2)生物组织测量的方法学进展。将进行研究，致力于改进和开发非侵入性量化生物组织的新方法。具体地说，将研究超声波准确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。三维计算机模拟能够量化和预测可能无法通过实验测量的结果。将开发人类运动的计算机模型，以研究肌肉控制的变化如何改变复杂的运动模式，特别是通过模拟疲劳的肌肉反应。这项研究计划的预期结果将为加拿大的自然科学和工程景观做出令人兴奋的、新颖的贡献。将确定有关肌肉策略的控制、协调和适应的创新进展及其对上肢运动的影响。我的研究项目的基本发现将对优化人类表现、预防肌肉和关节损伤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龄化的高度多样化的加拿大人口具有高度的相关性。