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

Bradley S. Davidson, Ph.D.

Second Advisor

Loren Cobb

Third Advisor

Peter Laz

Fourth Advisor

Mohammad Mahoor

Fifth Advisor

Nathan Sturtevant

Keywords

Kinematics, Lumbar spine, Positional MRI

Abstract

A more complete understanding of lumbar spine kinematics could improve diagnoses and treatment of low back pathologies and may advance the development of biomechanical models. Kinematics describes motion of the five lumbar vertebrae without consideration for the forces that cause the motion. Despite considerable attention from researchers and clinicians, lumbar spine kinematics are not fully understood because the anatomy is not accessible for direct observation and the complex governing biomechanics produce small magnitude, coupled intervertebral movements.

The overall goal of this project was to develop a descriptive model of intervertebral lumbar spine kinematics that is applicable to a generalizable subject population with diverse anthropometry. To accomplish this, a method was developed for measuring three-dimensional vertebral configuration using positional magnetic resonance imaging (MRI). The method makes use of automated vertebral registration to address time limitations in current data processing techniques and improves the ability to power experimental investigations.

Finally, a geometric model of lumbar vertebral kinematics was developed using principal component regression applied to in vivo vertebral measurement data across the range of flexion and extension joint motion. This principal component-based approach offers unique advantages for predicting and interpreting performance of complex systems such as lumbar joint biomechanics because no assumptions are made regarding the governing mechanisms. This provides an opportunity to infer mechanistic characteristics about intervertebral joint kinematics and to use in vivo data to validate musculoskeletal models.

Publication Statement

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

Rights Holder

Craig Joseph Simons

Provenance

Received from ProQuest

File Format

application/pdf

Language

en

File Size

94 p.

Discipline

Mechanical engineering, Biomechanics, Medical imaging and radiology

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