This paper compiles and analyzes some of the most current works related to upper limb prosthesis with emphasis on man-machine interfaces. A brief introduction of the basic subjects is given to explain what a prosthesis is, what types of prostheses exist, what they serve for, how they communicate with the user (control and feedback), and what technologies are involved. The method used in this review is also discussed, as well as the cataloging process and analysis of articles for the composition of this review. Each article is analyzed individually and its results are presented in a succinct way, in order to facilitate future research and serve as a source for professionals related to the area of prosthesis, such as doctors, engineers, researchers, and anyone interested in this subject. Finally, the needs and difficulties of the current prostheses, as well as the negative and positive points in the results are analyzed, and the progress achieved so far is discussed.

Mechanical hardness testing is fundamental in the evaluation of the mechanical properties of metallic materials due to the fact that the hardness values allow one to determine the wear resistance of the material involved, as well as the approximate values of its ductility, flow tension, among a number of other key characteristics. As a result, the main objective of the present work has been the development and analysis of a computational methodology capable of determining the Brinell and Vickers hardness value from hardness indentation images, which is based on image processing and analysis algorithms. In order to validate the methodology which has been developed, comparisons of the results resulting from the consideration of ten indentation image samples obtained through the conventional manual hardness measurement approach and a computational methodology have been carried out. This analysis allows one to conclude that the semi-automatic measurement of Vickers and Brinell hardness by the computational approach is easier, faster and less depended on the operator's subjectivity.

Resumo Introdução: Dentre as doenças que afetam a população mundial, destaca-se a preocupação com a Doença Pulmonar Obstrutiva Crônica (DPOC), que, segundo a Organizaç ã o Mundial de Saú de, pode se constituir na terceira causa de morte mais importante em todo mundo no ano de 2030. Visando contribuir com o auxílio ao diagnóstico médico, esta pesquisa centraliza seus esforços na etapa de segmentação dos pulmões, visto que esta é a etapa básica de sistema de Visão Computacional na area de pneumologia. Métodos: Este trabalho propõe um novo método de segmentação dos pulmões em imagens de Tomografi a Computadorizada (TC) do tórax chamado de Método de Contorno Ativo (MCA) Crisp Adaptativo 2D. Este MCA consiste em traçar automaticamente uma curva inicial dentro dos pulmões, que se deforma por iterações sucessivas, minimizando energias que atuam sobre a mesma, deslocando-a até as bordas do objeto. O MCA proposto é o resultado do aperfeiçoamento do MCA Crisp desenvolvido previamente, visando aumentar a sua exatidão, diminuindo o tempo de análise e reduzindo a subjetividade na segmentação e análise dos pulmões dessas imagens pelos médicos especialistas. Este método por iterações sucessivas de minimização de sua energia, segmenta de forma automática os pulmões em imagens de TC do tórax. Resultados: Para sua validação, o MCA Crisp Adaptativo é comparado com os MCAs THRMulti, THRMod, GVF, VFC, Crisp e também com o sistema SISDEP, sendo esta avaliação realizada utilizando como referência 24 imagens, sendo 12 de pacientes com DPOC e 12 de voluntários sadios, segmentadas manualmente por um pneumologista. Os resultados obtidos demonstram que o método proposto é superior aos demais. Conclusão: Diante dos resultados obtidos, pode-se concluir que este método pode integrar sistemas de auxílio ao diagnóstico médico na área de Pneumologia. Palavras-chave Auxílio ao diagnóstico médico, Método de Contorno Ativo, Segmentação do pulmão, Tomografi a computadorizada. Adaptive 2D Crisp Active Contour Model applied to lung segmentation in CT images of the thorax of healthy volunteers and patients with pulmonary emphysemaAbstract Introduction: Among the diseases that affect the world's population, there is concern about Chronic Obstructive Pulmonary Disease (COPD), that, according to the World Health Organization, could be the leading cause of death worldwide by the year 2030. Aiming to contribute to aid medical diagnosis, this research focuses its efforts on the segmentation of the lungs, since this is the basic step system in the area of Computer Vision pulmonology. Methods: This paper proposes a new method for segmentation of lung images in Computed Tomography (CT) of the chest called Active Contour Method (MCA) Crisp Adaptive 2D. This MCA is to draw a curve starting inside an object of interest. This curve is deformed by successive iterations, minimizing energies that act on it, moving it to the edges of the object. The MCA is the improvement of the proposed MCA Crisp previously developed, aiming to increase the accuracy, decreasing analysi...

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