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Abstract(s)
Este trabalho tem como principal finalidade a prevenção e o diagnóstico precoce de doenças que
afetam diretamente a planta do pé, como é o caso do pé diabético, que surge como consequência da
Diabetes Mellitus. Neste estudo, foi usada a técnica de termografia e foram adquiridas fotografias
termográficas de indivíduos com pés diabéticos e com pés saudáveis.
Recorre-se à otimização não linear para caracterizar a variação da temperatura dos dois tipos
de pé em estudo, sendo posteriormente feita uma comparação entre os resultados obtidos para os
mesmos. Foram usadas técnicas de otimização local e global. Para a otimização local foi explorado
o método Pattern Search e para a otimização global usaram-se os métodos Algoritmo Genético, o
Algoritmo Genético Híbrido e o Simulated Annealing.
São apresentados os resultados numéricos obtidos para as diferentes modelações testadas, através
de funções que definam a temperatura nas diversas regiões do pé.
The main aim of this work is the prevention and early diagnosis of diseases that directly affect the foot plant, such as diabetic foot, which arises as a consequence of the Diabetes Mellitus disease. In this study was used the technique of thermography and were acquired thermographic photographs of individuals with diabetic foot and healthy feet. To characterize the temperature variation of the two types of foot in this study, it was used the nonlinear optimization, and then was made a comparison between the results obtained for the same. Techniques of local and global optimization were used. For local optimization it was explored the Pattern Search method and for global optimization methods it was used the Genetic Algorithm, the Hybrid Genetic Algorithm and Simulated Annealing. The numerical results obtained for the different modulations tested through functions, that define the temperature in different regions of the foot, are presented.
The main aim of this work is the prevention and early diagnosis of diseases that directly affect the foot plant, such as diabetic foot, which arises as a consequence of the Diabetes Mellitus disease. In this study was used the technique of thermography and were acquired thermographic photographs of individuals with diabetic foot and healthy feet. To characterize the temperature variation of the two types of foot in this study, it was used the nonlinear optimization, and then was made a comparison between the results obtained for the same. Techniques of local and global optimization were used. For local optimization it was explored the Pattern Search method and for global optimization methods it was used the Genetic Algorithm, the Hybrid Genetic Algorithm and Simulated Annealing. The numerical results obtained for the different modulations tested through functions, that define the temperature in different regions of the foot, are presented.
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Keywords
Diabetes mellitus Termografia Otimização não linear Variação de temperatura