Computational Modeling of Stability and Laxity in the Natural and Implanted Knee Joint

The knee joint plays a central role in human motion for its dual function: providing a large range of motion in flexion/extension and stability in the other degrees of freedom. Computational modeling is a powerful tool to deepen our understanding of the joint mechanics, overcoming the main limitations of experimental investigations, i.e. time, cost and impracticability, and providing valuable insights for prosthetic design, rehabilitation and surgical planning. Within this background, the specific aim of this dissertation is threefold: to develop a sequentially-defined kinetostatic model of the knee, comparing the performance of spherical and anatomical surfaces; to develop a dynamic model of the knee to predict the quadriceps force during the squat activity; to estimate the compressive force that the implanted knee joint needs in order to reproduce natural stability. This dissertation presents novel and efficient procedures to model and evaluate the behavior of the natural and implanted knee under the effect of static and dynamic loading conditions, extending the current knowledge in the field of musculoskeletal computational modeling.