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Wearable computing is a form of ubiquitous computing that offers flexible and useful tools for users. Specifically, glove-based systems have been used in the last 30 years in a variety of applications, but mostly focusing on sensing people's attributes, such as finger bending and heart rate. In contrast, we propose in this work a novel flexible and reconfigurable instrumentation platform in the form of a glove, which can be used to analyze and measure attributes of fruits by just pointing or touching them with the proposed glove. An architecture for such a platform is designed and its application for intuitive fruit grading is also presented, including experimental results for several fruits.

Resumo Introdução: A Esclerose Lateral Amiotrófica (ELA) é uma doença neurodegenerativa, caracterizada por uma progressiva e fatal perda de neurônios motores do córtex cerebral, tronco encefálico e medula espinhal, mas que mantém preservada a atividade intelectual e cognitiva do paciente. Pacientes acometidos por essa doença irão invariavelmente necessitar do auxílio de ventiladores mecânicos. Métodos: Foi utilizado um conjunto de hardware e software para realizar o monitoramento dos parâmetros respiratórios dos pacientes em leitos hospitalares como forma de auxiliar à equipe de saúde. O monitoramento desses parâmetros deu-se por meio de uma webcam, que capturava os valores exibidos na tela do ventilador mecânico, e do emprego de técnicas de visão computacional e Optical Character Recognition (OCR). Neste sentido, o sistema foi testado sob três condições de luminosidade diferentes para verificar a eficácia do mesmo. Resultados: O sistema apresentou uma média geral de acertos de 94.90%. Além disso, quando a interferência luminosa foi mínima, o sistema obteve uma média geral de acertos de 97,76%. Conclusão: A adoção de um sistema computacional baseado em visão computacional para auxílio da equipe de saúde no monitoramento hospitalar de pacientes com ELA mostrou-se satisfatória. No entanto, a pesquisa mostrou que a adoção de um sistema com maior imunidade à interferências luminosas externas tende a apresentar melhores resultados. Palavras-chave Monitoramento de pacientes, Esclerose Lateral Amiotrófica, BiPAP, Visão computacional, Ambiente WEB, Computador de placa única. An angel for ALS: architecture based on computer vision applied for on-line monitoring respiratory parameters of patients with Amyotrophic Lateral Sclerosis (ALS) in hospital environment Abstract Introduction: Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by a progressive and fatal loss of motor neurons in the cerebral cortex, brainstem and spinal cord. In spite of that, the patient's intellectual and cognitive activity remains preserved. Patients affected by this disease will invariably need the help of mechanical ventilators. Methods: A set of hardware and software was used to perform the monitoring of respiratory parameters of patients in hospital beds as a means of assisting the healthcare team. The monitoring of these parameters was performed by a webcam that captured the values displayed on the screen of the ventilator, and the employment of computer vision techniques and Optical Character Recognition (OCR). In this sense, the system was tested under three different lighting conditions to verify its effectiveness. Results: The system presented an overall average of 94.90% of correct answers. Furthermore, when the luminous interference was minimum, it achieved an overall average of success of 97.76%. Conclusion: The adoption of a computational system based on computer vision to aid the healthcare team in hospital monitoring of patients with ALS was satisfactory. However, the research has shown that the adoption...

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