Date of Award
Daniel Felix Ritchie School of Engineering and Computer Science
Peter J. Laz, Ph.D.
Customized implant, Finite element analysis, Kinematics predictions, Knee joint, Population-based variability, Statistical shape model
Prior statistical shape models have not considered multiple structures in the knee joint to characterize anatomic variation which are required to investigate joint mechanics further for the successful knee replacement. Accordingly, the study's objective was to develop statistical shape and alignment model (SSAM) to capture intersubject variability and demonstrate the ability to generate realistic instances for use in finite element analysis (FEA). SSAM described the variability in the training set of 20 subjects with a series of modes of variation obtained by performing principal component analysis (PCA). PCA produced modes of variation with the first 3 modes representing 70% and 10 modes representing 95% variability when only bones of the joint were studied. Modes were perturbed by ± 2ó and computational models of new virtual subjects were generated. FEA successfully confirmed the fidelity of the SSAM approach. The relationship between SSAM and function (motion) were investigated through the shape-function model. The framework can create new subject and predict the kinematic behavior. The approach can be an investigative tool to differentiate in the shape-function relation between healthy normal and pathologic groups.
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Received from ProQuest
Rao, Chandreshwar, "Representing Intersubject Variability with a Statistical Shape and Alignment Model of the Knee" (2013). Electronic Theses and Dissertations. 907.
Biomechanics, Mechanical Engineering, Statistics