Um ambiente de suporte ao trabalho cooperativo com aplicação à telemedicina

This dissertation presents a cooperative virtual multimedia enviroment for employing on time medical Field, using a TCP/IP computer network. The Virtual Diagnosis Room environment make it possible to perform cooperative tasks using classical image processing. Synchronous and assynchronous text conversation (chat) and content markup, in order to produce remote cooperative diagnosis. The dissertation also describes the tool in detail and its functions, that enables the interaction among users, along with implementation detals, contributions and weakness of this work

Análise de desempenho na rede metropolitana de saúde da Universidade Federal do Rio Grande do Norte : um dimensionamento aplicado a telemedicina e a telessaúde utilizando QoS baseado no padrão IEEE 802.1Q

It s notorious the advance of computer networks in recent decades, whether in relation to transmission rates, the number of interconnected devices or the existing applications. In parallel, it s also visible this progress in various sectors of the automation, such as: industrial, commercial and residential. In one of its branches, we find the hospital networks, which can make the use of a range of services, ranging from the simple registration of patients to a surgery by a robot under the supervision of a physician. In the context of both worlds, appear the applications in Telemedicine and Telehealth, which work with the transfer in real time of high resolution images, sound, video and patient data. Then comes a problem, since the computer networks, originally developed for the transfer of less complex data, is now being used by a service that involves high transfer rates and needs requirements for quality of service (QoS) offered by the network . Thus, this work aims to do the analysis and comparison of performance of a network when subjected to this type of application, for two different situations: the first without the use of QoS policies, and the second with the application of such policies, using as scenario for testing, the Metropolitan Health Network of the Federal University of Rio Grande do Norte (UFRN)

Fuzzy angel: uma arquitetura distribuída de telemedicina para monitoramento de pacientes com esclerose lateral amiotrófica

The Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by progressive muscle weakness that leads the patient to death, usually due to respiratory complications. Thus, as the disease progresses the patient will require noninvasive ventilation (NIV) and constant monitoring. This paper presents a distributed architecture for homecare monitoring of nocturnal NIV in patients with ALS. The implementation of this architecture used single board computers and mobile devices placed in patient’s homes, to display alert messages for caregivers and a web server for remote monitoring by the healthcare staff. The architecture used a software based on fuzzy logic and computer vision to capture data from a mechanical ventilator screen and generate alert messages with instructions for caregivers. The monitoring was performed on 29 patients for 7 con-tinuous hours daily during 5 days generating a total of 126000 samples for each variable monitored at a sampling rate of one sample per second. The system was evaluated regarding the rate of hits for character recognition and its correction through an algorithm for the detection and correction of errors. Furthermore, a healthcare team evaluated regarding the time intervals at which the alert messages were generated and the correctness of such messages. Thus, the system showed an average hit rate of 98.72%, and in the worst case 98.39%. As for the message to be generated, the system also agreed 100% to the overall assessment, and there was disagreement in only 2 cases with one of the physician evaluators.

Fuzzy angel: uma arquitetura distribuída de telemedicina para monitoramento de pacientes com esclerose lateral amiotrófica

The Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by progressive muscle weakness that leads the patient to death, usually due to respiratory complications. Thus, as the disease progresses the patient will require noninvasive ventilation (NIV) and constant monitoring. This paper presents a distributed architecture for homecare monitoring of nocturnal NIV in patients with ALS. The implementation of this architecture used single board computers and mobile devices placed in patient’s homes, to display alert messages for caregivers and a web server for remote monitoring by the healthcare staff. The architecture used a software based on fuzzy logic and computer vision to capture data from a mechanical ventilator screen and generate alert messages with instructions for caregivers. The monitoring was performed on 29 patients for 7 con-tinuous hours daily during 5 days generating a total of 126000 samples for each variable monitored at a sampling rate of one sample per second. The system was evaluated regarding the rate of hits for character recognition and its correction through an algorithm for the detection and correction of errors. Furthermore, a healthcare team evaluated regarding the time intervals at which the alert messages were generated and the correctness of such messages. Thus, the system showed an average hit rate of 98.72%, and in the worst case 98.39%. As for the message to be generated, the system also agreed 100% to the overall assessment, and there was disagreement in only 2 cases with one of the physician evaluators.

Método Fuzzy para auxílio ao diagnóstico de câncer de mama em ambiente inteligente de telediagnóstico colaborativo para apoio à tomada de decisão

Breast cancer, despite being one of the leading causes of death among women worldwide is a disease that can be cured if diagnosed early. One of the main techniques used in the detection of breast cancer is the Fine Needle Aspirate FNA (aspiration puncture by thin needle) which, depending on the clinical case, requires the analysis of several medical specialists for the diagnosis development. However, such diagnosis and second opinions have been hampered by geographical dispersion of physicians and/or the difficulty in reconciling time to undertake work together. Within this reality, this PhD thesis uses computational intelligence in medical decision-making support for remote diagnosis. For that purpose, it presents a fuzzy method to assist the diagnosis of breast cancer, able to process and sort data extracted from breast tissue obtained by FNA. This method is integrated into a virtual environment for collaborative remote diagnosis, whose model was developed providing for the incorporation of prerequisite Modules for Pre Diagnosis to support medical decision. On the fuzzy Method Development, the process of knowledge acquisition was carried out by extraction and analysis of numerical data in gold standard data base and by interviews and discussions with medical experts. The method has been tested and validated with real cases and, according to the sensitivity and specificity achieved (correct diagnosis of tumors, malignant and benign respectively), the results obtained were satisfactory, considering the opinions of doctors and the quality standards for diagnosis of breast cancer and comparing them with other studies involving breast cancer diagnosis by FNA.

Um estudo e análise do teste de emissões otoacústicas realizadas através de uma plataforma móvel

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES