RESUMEN
An ARM-based embedded system design schemes is proposed for the color-blind image processing system. The hardware and software of the embedded color-blind image processing system are designed using ARM core processor. Besides, a simple and convenient interface is implemented. This system supplies a general hardware platform for the applications of color-blind image processing algorithms, so that it may bring convenience for the test and rectification of color blindness.
Asunto(s)
Algoritmos , Defectos de la Visión Cromática , Diagnóstico , Diseño de Equipo , Procesamiento de Imagen Asistido por Computador , Métodos , Programas InformáticosRESUMEN
The effects of loading conditions on the structural capacity of the proximal femur were investigated parametrically by Finite Element Analysis (FEA) combined with Hoffman failure criterion. The loading conditions included the fall configuration angles, load locations and the friction resistance in hip joint. The results of this parametric study revealed that the load locations are the keys to determining the structural capacity of the proximal femur. There are two low peaks of the structural capacity when the loads are applied to femoral head. If the impact load were applied in this area, the fracture risk would be great. The frictional resistance of the hip joint can severely affect the failure load, which has far reaching implications in terms of osteoarthritis.
Asunto(s)
Humanos , Accidentes por Caídas , Fenómenos Biomecánicos , Simulación por Computador , Fémur , Fisiología , Análisis de Elementos Finitos , Fracturas de Cadera , Modelos Biológicos , Medición de Riesgo , Estrés Mecánico , Soporte de PesoRESUMEN
Femur fracture from falls is considered one of the most serious types of the elderly. FEA has proved to be an extremely useful tool in the structure analysis of the proximal femur. In this paper, a FEA model of proximal femur is introduced, and Hoffman failure criteria are built based on the experimental strength data for both cortical bone and trabecular bone of the femur from some references. The FEA model and the failure criteria are verified using other researcher's experimental results. The predicted trabecular failure load was only 0.5% lower than the experimental data and cortical failure load was 4.2% higher than the experimental result. This result shows that our FEA model, combined with the Hoffman criterion for both cortical bone and trabecular bone, can effectively predict the structural capacity of the femur during falling.