Next-generation computational models to understand human joints

理解人体关节的下一代计算模型

• 批准号: FT230100524
• 负责人: A/Prof Dominic Thewlis
• 金额: $ 75.31万
• 依托单位: The University of Adelaide
• 依托单位国家: 澳大利亚
• 项目类别: ARC Future Fellowships
• 财政年份: 2023
• 资助国家: 澳大利亚
• 起止时间: 2023-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/FT230100524
• 关键词: Next; generation; computational; models; understand

This project aims to investigate human joint systems through combining state-of-the-art imaging and high-fidelity biomechanical models. The methods developed in this project are expected to generate new ways of studying the dynamic response of musculoskeletal tissues to activity, including how musculoskeletal physiology can adapt to biomechanical stimuli. Expected outcomes include establishing a non-invasive method for characterising whole joint systems. This project will provide significant knowledge gain on the biomechanical regulation of human joints across form, function, dynamics and loading which may help across many facets of society to guide physical activity choices.

该项目旨在通过结合最先进的成像和高保真生物力学模型来研究人体关节系统。该项目开发的方法预计将产生研究肌肉骨骼组织对活动的动态响应的新方法，包括肌肉骨骼生理学如何适应生物力学刺激。预期结果包括建立一种非侵入性方法来表征整个关节系统。该项目将提供有关人类关节在形式、功能、动力学和负载方面的生物力学调节的重要知识，这可能有助于社会的许多方面指导身体活动的选择。