Hip fracture is the most common reason for admission to an orthopaedic trauma word. It is usually a 'Fragility' fracture caused by a fall affecting an older person with osteoporosis or osteopenia (a condition in which bones lose calcium and become thinner, but not as much as in osteoporosis). The National Hip Fracture Database worldwide reports the average age of a person with hip fracture is 84 years for men and 83 years for women, 76% of fracture occurs in women. By 2050, the worldwide incidence of hip fracture in men is projected to increase by 24% in women and 31% in men. Hip fractures due to sideways falls are a worldwide health problem, especially amongst elderly people. The experienced force to the proximal femur during a fall leading to hip fracture is significantly dependent on density, thickness and stiffness of the body during impact. The process of fracture and healing can only be understood in terms of structure and composition of the bone and also its mechanical properties. Bone fracture analysis investigates to predict various failure mechanisms under different loading conditions. In an effort to improve and assist scientists and researchers to predict the impact damage response of bone structures and estimate femoral fracture load in vitro, an accurate explicit finite element (14E) method has been investigated in this study. In the first part, the main goal is to create a 3D reconstruction and registration of semi-transparent Computed Tomography (CT) scan image data using SIMPLEWARE software. In the second part, effect of cortical thickness and impact velocity on the energy absorption of hip during a fall has been investigated on a 3D model. Additionally composite femora were mechanically tested to failure and regression analyses between measured fracture load and FE-predicted fracture load were performed. The results indicate that this sophisticated technique, which is still early in its development, can achieve precision comparable to that of densitometry and can predict femoral fracture load to within 18% with 95% confidence.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:617374 |
| Date | January 2014 |
| Creators | Razmkhah, Omid |
| Contributors | Aboutorabi, Akbar ; Ghasemnejad, Hessam |
| Publisher | Kingston University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://eprints.kingston.ac.uk/28910/ |
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