Revealing structure-function relationships with computational models of the human body

在这个研究项目中，我将大大提高速度，保真度和预测能力的计算机模型的身体，涉及硬组织和软组织结构的相互作用，包括脊柱，肩膀和脸。我在建模方面的突破性进展将为这些复杂的生物力学系统如何发挥作用创造前所未有的见解，并有助于指导加拿大人遭受痛苦的肌肉骨骼损伤的康复。 健康的背部功能需要脊柱的硬组织和软组织结构之间的正确相互作用：椎骨与分开它们的软椎间盘以及移动和支撑它们的肌肉和韧带相互作用。软组织和硬组织之间同样的相互作用发生在整个身体。一个值得注意的例子是面部，我们最夸张的表情和最微妙的表情都是由头骨和颌骨支撑的软面部组织完成的。另一个例子是肩膀，一个非常不稳定的“球窝”是由肌肉和韧带组成的。脊柱、肩膀和面部都是非常复杂的生物力学系统，仅通过测量很难理解。计算机模型可以帮助我们理解这些系统中的运动和力量，并揭示结构和功能之间的潜在关系。然而，目前的生物力学建模方法不适合耦合的软硬组织系统，如脊柱，面部和肩部。我将重点介绍三种建模技术。我将研究快速有限元方法，这是目前软组织模拟的瓶颈。我将开发新的方法来处理动态约束，这是需要捕捉关节表面之间的接触和软硬组织的机械耦合。最后，我将开发新的面部、肩部和脊柱运动的学习模型，通过数百万次计算机模拟训练，实时生成可靠的预测。这些技术将被用于创建世界上最具表现力的虚拟面部动画，在受伤最频繁的关节中进行接触模拟的肩部模型，以及实时模拟脊椎骨，软组织椎间盘和数百块肌肉之间相互作用的脊柱模型。我将在9个项目中培训16名HQP，重点是用于人体建模的高级模拟和机器学习技术。他们的研究将导致身体机制的突破性发现和模拟这些机制的新技术的发明。该计划将通过推进我们在机器学习，自动化，机器人，医疗设备，计算机动画和视频游戏等高科技领域使加拿大受益。它还将通过发明新的计算机工具来积极影响加拿大人的生活，这些工具可以指导患有背部和肩部问题的个人的个性化康复。

In this research program, I will dramatically improve the speed, fidelity and predictive power of computer models of the body that involve an interaction of hard and soft tissue structures, including the spine, shoulder, and face. My breakthrough advances in modeling will create unprecedented insights into how these complex biomechanical systems function, and help to guide rehabilitation for Canadians suffering from painful musculoskeletal injuries. Healthy back function requires the correct interaction between hard and soft tissue structures of the spine: the vertebrae interacting with the soft discs that separate them and the muscles and ligaments that move and stiffen them. The same interplay between soft and hard tissues occurs throughout the body. One notable example is the face, where our most exaggerated expressions, and our most subtle, are accomplished by soft facial tissues supported underneath by the skull and jaw bones. Another example is the shoulder, where a very unstable "ball-and-socket" is supported by a concert of muscles and ligaments. The spine, shoulder, and face are each incredibly intricate and complex biomechanical systems, which are difficult to understand by measurements alone. Computer models can help our understanding by allowing us to visualize movements and forces in these systems and revealing the underlying relationships between structure and function. However, current methods for biomechanical modeling fall short for coupled soft-hard tissue systems, like the spine, face, and shoulder. I will focus on advancing three modeling techniques. I will investigate fast finite-element methods, which are the current bottleneck in soft-tissue simulation. I will develop new ways to handle dynamic constraints, which are needed to capture contact between joint surfaces and the mechanical coupling of soft and hard tissues. Finally, I will develop novel learned models of face, shoulder and spine movements, trained with millions of computer simulations, to generate reliable predictions in real-time. These techniques will be used to create the world's most expressive virtual face animations, a shoulder model with contact simulation in the joint where injuries are most frequent, and a spine model that simulates the interaction between vertebral bones, soft-tissue discs, and hundreds of muscles in real-time. I will train 16 HQP in 9 projects focusing on advanced simulation and machine learning techniques for human modeling. Their research will lead to breakthrough discoveries of the mechanisms of the body and invention of new technologies for simulating those mechanisms. This program will benefit Canada by advancing our high-tech sectors in machine learning, automation, robotics, medical devices, computer animation, and video games. It will also positively affect the lives of Canadians by inventing new computer tools that can guide personalized rehabilitation for individuals suffering from back and shoulder problems.