Author: Raissa Katembwe
Katembwe, Raissa, 2017 THE RELATIONSHIP BETWEEN FEMUR MECHANICS AND MOVEMENT, Flinders University, School of Computer Science, Engineering and Mathematics
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For more than a few decades, the investigation of femoral strain has been an active area of study in the biomechanical field. This is because a large number of people are globally affected yearly by femur fracture which is a mechanically related pathology. Therefore, it is vital to understand how strain in the bone is a function of geometry and loads which is dependent on the type of activity the person is performing. This project was privileged to use readily available data from a previous study. The data comprised of twenty-two healthy post-menopausal women aged between 60-77 years who had computer tomograph scans of finite element models taken. Additionally, gait data of weight-bearing tasks such as standing up and siting on a chair, walking up and down the stairs, jumping, walking and fasting walking performed by each subject were also collected. The aim of this project was to analyse the data available to understand the relationship between femoral strains and activities as this was rather unclear. Two steps were involved; firstly, multiple regression was undertaken to understand the relationship between strain distribution during various activities. Secondly, principal component analysis describing the variations that were possible within geometry was performed. The findings from the multiple regression suggested that daily activities explain 91% of the variations of strains across subjects. Thus proposing that geometry and material bone properties attribute about 9% to the strain distribution in the femur. On the other hand, the findings from principle component analysis indicate that the first 5 modes captured about 93% of the variations of geometry in the training set; this is to state that these modes account for most of the variance in the observed variable. The results obtained in this project demonstrate that the activity a person undertakes is of major importance on the strains exhibited in the femur. However, the results obtained require further analysis to be validated. Nonetheless the next steps in the project would be to incorporate multiple regression analysis and principal component analysis of geometry and material properties to determine the relationship between activities and bone stiffness in relation to strain and determine how simplified information has an impact on strain. For more than a few decades, the investigation of femoral strain has been an active area of study in the biomechanical field. This is because a large number of people are globally affected yearly by femur fracture which is a mechanically related pathology. Therefore, it is vital to understand how strain in the bone is a function of geometry and loads which is dependent on the type of activity the person is performing. This project was privileged to use readily available data from a previous study. The data comprised of twenty-two healthy post-menopausal women aged between 60-77 years who had computer tomograph scans of finite element models taken. Additionally, gait data of weight-bearing tasks such as standing up and siting on a chair, walking up and down the stairs, jumping, walking and fasting walking performed by each subject were also collected. The aim of this project was to analyse the data available to understand the relationship between femoral strains and activities as this was rather unclear. Two steps were involved; firstly, multiple regression was undertaken to understand the relationship between strain distribution during various activities. Secondly, principal component analysis describing the variations that were possible within geometry was performed. The findings from the multiple regression suggested that daily activities explain 91% of the variations of strains across subjects. Thus proposing that geometry and material bone properties attribute about 9% to the strain distribution in the femur. On the other hand, the findings from principle component analysis indicate that the first 5 modes captured about 93% of the variations of geometry in the training set; this is to state that these modes account for most of the variance in the observed variable. The results obtained in this project demonstrate that the activity a person undertakes is of major importance on the strains exhibited in the femur. However, the results obtained require further analysis to be validated. Nonetheless the next steps in the project would be to incorporate multiple regression analysis and principal component analysis of geometry and material properties to determine the relationship between activities and bone stiffness in relation to strain and determine how simplified information has an impact on strain.
Keywords: femoral strains, daily activities, PCA and MLR
Subject: Engineering thesis
Thesis type: Masters
Completed: 2017
School: School of Computer Science, Engineering and Mathematics
Supervisor: Dr Saulo Martelli