Date of Award

1-1-2013

Document Type

Masters Thesis

Degree Name

M.S.

Organizational Unit

Daniel Felix Ritchie School of Engineering and Computer Science

First Advisor

Peter J. Laz, Ph.D.

Second Advisor

Paul Rullkoetter

Third Advisor

Alvaro Arias

Keywords

Customized implant, Finite element analysis, Kinematics predictions, Knee joint, Population-based variability, Statistical shape model

Abstract

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.

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Chandreshwar Rao

Provenance

Received from ProQuest

File Format

application/pdf

Language

en

File Size

93 p.

Discipline

Biomechanics, Mechanical Engineering, Statistics

Download



Share

COinS