Multivariate Techniques in Biomechanical Analysis


Autoria(s): Hassan, ELIZABETH
Contribuinte(s)

Queen's University (Kingston, Ont.). Theses (Queen's University (Kingston, Ont.))

Data(s)

03/08/2016

04/08/2016

04/08/2016

04/08/2016

Resumo

This work outlines the theoretical advantages of multivariate methods in biomechanical data, validates the proposed methods and outlines new clinical findings relating to knee osteoarthritis that were made possible by this approach. New techniques were based on existing multivariate approaches, Partial Least Squares (PLS) and Non-negative Matrix Factorization (NMF) and validated using existing data sets. The new techniques developed, PCA-PLS-LDA (Principal Component Analysis – Partial Least Squares – Linear Discriminant Analysis), PCA-PLS-MLR (Principal Component Analysis – Partial Least Squares –Multiple Linear Regression) and Waveform Similarity (based on NMF) were developed to address the challenging characteristics of biomechanical data, variability and correlation. As a result, these new structure-seeking technique revealed new clinical findings. The first new clinical finding relates to the relationship between pain, radiographic severity and mechanics. Simultaneous analysis of pain and radiographic severity outcomes, a first in biomechanics, revealed that the knee adduction moment’s relationship to radiographic features is mediated by pain in subjects with moderate osteoarthritis. The second clinical finding was quantifying the importance of neuromuscular patterns in brace effectiveness for patients with knee osteoarthritis. I found that brace effectiveness was more related to the patient’s unbraced neuromuscular patterns than it was to mechanics, and that these neuromuscular patterns were more complicated than simply increased overall muscle activity, as previously thought.

Thesis (Ph.D, Mechanical and Materials Engineering) -- Queen's University, 2016-08-03 15:53:40.518

Identificador

http://hdl.handle.net/1974/14684

Idioma(s)

en

en

Relação

Canadian theses

Direitos

Queen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canada

ProQuest PhD and Master's Theses International Dissemination Agreement

Intellectual Property Guidelines at Queen's University

Copying and Preserving Your Thesis

This publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.

Palavras-Chave #multivariate #biomechanics
Tipo

Thesis