Development of a Statistical Shape-Function Model of the Implanted Knee to Predict Joint Mechanics

Outcomes of total knee replacement are dependent on surgical technique, patient variability, and implant design. Non-optimal design choices may result in undesirable contact mechanics and joint kinematics. Specifically, the design process requires significant investments of time, software, and expertise for even a single iteration. Our objective was the development of a statistical shape-function model of a posterior stabilized knee implant to predict output mechanics in a resource efficient matter. Finite element methods were combined with design of experiments to produce predictive models relating nine implant design parameters to key outputs for a tibial-femoral joint performing a squat cycle