CAREER: Scalable Musculoskeletal Simulation for Biomechanical Animation
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This project will build new computational models for biomechanically based animation of digital humans, suitable for a wide range of applications. Beyond computer animation, the result of this research will be used for anatomy training and education by combining musculoskeletal simulations with haptic feedback. This research will also lead to novel applications in diverse other fields, including: medicine, for surgical training and stroke rehabilitation; ergonomics, for better understanding of energy use; bio-paleontology, for discovering the movement of extinct animals; robotics, for bio-inspired tendon-driven actuators; and neuroscience, for reverse engineering the brain by providing a computational testbed for understanding motor control. The integrated educational objective of this project is to use concepts from computer graphics, computer animation, and computational biomechanics as motivational tools to teach people of diverse ages and backgrounds about STEM careers.This research will build on existing musculoskeletal simulations in biomechanics and graphics. In recent decades, two contrasting methods for musculoskeletal simulation have been developed: line-based methods and volume-based methods. Unfortunately, there is currently no way to get the best of both worlds because these methods are built on fundamentally different principles; line-based methods are built on rigid body dynamics, whereas volume-based methods are built on continuum mechanics. This project will bridge the gap between these two approaches. The specific research objectives are threefold. (1) To imbue the standard line-based methods with two important features, muscle inertia and branching. The guiding principle for this research objective is to expand the current capabilities of existing line-based methods while enabling easy integration into off-the-shelf simulators. (2) To apply intelligent model reduction that is specific to muscles, in order to make the volume-based methods more efficient and robust, and capable of gracefully degrading to line-based methods. (3) To validate the proposed computational models rigorously with real-world anatomical data.This award reflects NSF''s statutory mission and has been deemed worthy of support through evaluation using the Foundation''s intellectual merit and broader impacts review criteria.