Lloyd David
School of Health Sciences and Social Work, Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), in the Menzies Health Institute Queensland and Advanced Design and Prototyping Technologies Institute, Griffith University, Australia.
Sports Biomech. 2024 Oct;23(10):1284-1312. doi: 10.1080/14763141.2021.1959947. Epub 2021 Sep 8.
This paper explores the use of biomechanics in identifying the mechanistic causes of musculoskeletal tissue injury and degeneration. It appraises how biomechanics has been used to develop training programmes aiming to maintain or recover tissue health. Tissue health depends on the functional mechanical environment experienced by tissues during daily and rehabilitation activities. These environments are the result of the interactions between tissue motion, loading, biology, and morphology. Maintaining health of and/or repairing musculoskeletal tissues requires targeting the "ideal" tissue mechanics (i.e., loading and deformation), which may be enabled by appropriate real-time biofeedback. Recent research shows that biofeedback technologies may increase their quality and effectiveness by integrating a personalised neuromusculoskeletal modelling driven by real-time motion capture and medical imaging. Model personalisation is crucial in obtaining physically and physiologically valid predictions of tissue biomechanics. Model real-time execution is crucial and achieved by code optimisation and artificial intelligence methods. Furthermore, recent work has also shown that laboratory-based motion capture biomechanical measurements and modelling can be performed outside the laboratory with wearable sensors and artificial intelligence. The next stage is to combine these technologies into well-designed easy to use products to guide training to maintain or recover tissue health in the real-world.
本文探讨了生物力学在确定肌肉骨骼组织损伤和退变的机制原因方面的应用。它评估了生物力学如何被用于制定旨在维持或恢复组织健康的训练计划。组织健康取决于组织在日常活动和康复活动中所经历的功能性力学环境。这些环境是组织运动、负荷、生物学和形态学之间相互作用的结果。维持和/或修复肌肉骨骼组织的健康需要针对“理想的”组织力学（即负荷和变形），这可以通过适当的实时生物反馈来实现。最近的研究表明，生物反馈技术可以通过整合由实时运动捕捉和医学成像驱动的个性化神经肌肉骨骼模型来提高其质量和有效性。模型个性化对于获得组织生物力学的物理和生理有效预测至关重要。模型实时执行至关重要，可通过代码优化和人工智能方法实现。此外，最近的研究还表明，基于实验室的运动捕捉生物力学测量和建模可以通过可穿戴传感器和人工智能在实验室外进行。下一阶段是将这些技术整合到精心设计、易于使用的产品中，以指导训练，在现实世界中维持或恢复组织健康。
