High-Fidelity Simulation of Human Muscles and Movement

高保真模拟人体肌肉和运动

• 批准号: 402241-2013
• 负责人: Stavness, Ian
• 金额: $ 1.46万
• 依托单位: University of Saskatchewan
• 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=665855
• 关键词: Fidelity; Simulation; Human; Muscles; Movement

Physics-based computer animation has improved our ability to simulate natural phenomena such as colliding objects, splashing waves, and moving characters. Although these simulation techniques can create compelling special effects for movies and games, the practical use of computer simulation in product design, ergonomics, and medicine remains very limited. In order for simulations to have significant impact beyond animation, they must not only be visually appealing, but also physically accurate and evaluated with experimental data. The proposed research program seeks to improve and evaluate the physical accuracy of human body simulations for applications in biomechanics. Our results will overcome the current limitations of human body simulation and improve our ability to diagnose movement disorders, guide rehabilitation, and train athletes.** Two short-term research goals address fundamental limitations of current biomechanics simulations: simplistic visualizations and low-fidelity muscle models. We will create new techniques to visualize internal muscle deformations, realistic face animations, and exaggerated yet plausible character movements. We will also improve the fidelity of complex muscle models, such as those with feather-like structures, internal tendons, and broad attachment areas, to improve predictions of how muscle forces are generated and distributed. To verify our techniques and validate our results, our visualizations and simulations will be compared with measurements from real humans.** This research will have considerable impact. The proposed projects will raise the bar for human simulation in terms of visualization richness, muscle detail, and evaluation methodology. Our computational methods and models will be widely disseminated through two world-leading, open-source software projects: ArtiSynth at UBC and OpenSim at Stanford University. In the long term, we aim to achieve a deeper understanding of human biomechanics that will greatly increase the predictive power of computer simulation for animation, training, diagnosis, and treatment planning.

基于物理的计算机动画提高了我们模拟自然现象的能力，例如碰撞物体，飞溅的波浪和移动的角色。虽然这些仿真技术可以为电影和游戏创造引人注目的特效，但计算机仿真在产品设计，人体工程学和医学中的实际应用仍然非常有限。为了使模拟具有超越动画的重大影响，它们不仅必须具有视觉吸引力，而且必须具有物理准确性并使用实验数据进行评估。拟议的研究计划旨在提高和评估人体模拟在生物力学应用中的物理准确性。我们的研究结果将克服目前人体模拟的局限性，提高我们诊断运动障碍、指导康复和训练运动员的能力。 两个短期研究目标解决了当前生物力学模拟的基本局限性：简单的可视化和低保真度的肌肉模型。我们将创造新的技术来可视化内部肌肉变形，逼真的面部动画，以及夸张但合理的角色动作。我们还将提高复杂肌肉模型的保真度，例如具有羽毛状结构，内部肌腱和广泛附着区域的模型，以改善对肌肉力量如何产生和分布的预测。为了验证我们的技术和验证我们的结果，我们的可视化和模拟将与真实的人类的测量结果进行比较。 这项研究将产生相当大的影响。拟议中的项目将在可视化丰富性，肌肉细节和评估方法方面提高人体模拟的标准。我们的计算方法和模型将通过两个世界领先的开源软件项目广泛传播：UBC的ArtiSynth和斯坦福大学的OpenSim。从长远来看，我们的目标是更深入地了解人体生物力学，这将大大提高计算机模拟对动画，培训，诊断和治疗计划的预测能力。