Implementação em tempo real de um sistema de reconhecimento de digitos conectados

Orientador: Luis Geraldo Pedroso MeloniDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de ComputaçãoMestrad

Raspcare: A Telemedicine Platform for the Treatment and Monitoring of Patients with Chronic Diseases

Metabolic and electrophysiological measures must remain within normal values to maintain the quality of life of chronic patients. Furthermore, depending on the age and disease stage of the individual, automatic identification of risk situations is critical for emergency support. To achieve these goals, this study proposes a technological solution termed Raspcare to help both the patients in their self-care and the medical teams monitoring the patients. The solution consists of a domestic gateway equipped with a microcontroller and various interfaces to allow interaction between the platform and household devices, such as televisions, biometric sensors, blood glucose metres, non-invasive pressure gauges, smartphones and smartwatches, among others. The gateway implements a Linux OS application responsible for executing the user’s health plan, which involves periodic measurements, medications and dietary care. Moreover, the application has data processing algorithms to establish alerts for the automatic detection of abnormal measurements and falls

Uso de tecnologias de Telessaúde por médicos do Programa Mais Médicos e fatores associados – Espírito Santo, 2016

Telehealth is key to primary health care qualification. There is no knowledge about its use in the Mais Médicos Program. Here, we sought to analyze the use of Telehealth tools at Mais Médicos in Espírito Santo state in 2016. This is a cross-sectional study with a structured questionnaire applied to the total number of physicians present at regional telehealth seminars. The analysis included absolute and relative frequency and bivariate analysis with Fisher's exact test. As a result, 211 doctors (48.6% of the total number of professionals at Mais Médicos) participated. The majority were Cubans who worked in a large urban center with a specialization in Family and Community Medicine. Most (n=130, 61.9%) had already used some Telehealth service, but discontinuously, with Tele-education being the most used (n=101; 77.7%). Getting to know Telehealth and its tools and seeing them as relevant to improving the service were associated with greater use of technologies. The facility and type of device used to access the internet do not influence the use of the program. It is concluded that the knowledge and relevance given to Telehealth tools by professionals and their work context are more associated with their use than structural working conditions.Telessaúde é uma das estratégias de qualificação da atenção primária. Não há trabalho que analise sua utilização no Programa Mais Médicos. Logo, buscou-se analisar a utilização das ferramentas de Telessaúde no Mais Médicos do estado Espírito Santo em 2016. Trata-se de um estudo transversal com aplicação de questionário estruturado ao total de médicos presentes em seminários regionais em Telessaúde. A análise incluiu frequência absoluta e relativa e análise bivariada com teste exato de Fisher. Como resultado, 211 médicos (48,6% do total de profissionais do Mais Médicos) participaram, sendo a maioria cubanos que atuavam em grande centro urbano com especialização em Medicina de Família e Comunidade. A maior parte (n=130, 61,9%) já havia utilizado algum serviço de Telessaúde, mas de forma descontínua, sendo a teleducação o mais utilizado (n=101; 77,7%). Conhecer o Telessaúde e suas ferramentas e vê-las como relevantes para a melhoria do serviço se associaram a maior uso das tecnologias. A facilidade e o tipo de dispositivo utilizado para acessar a internet não influenciam a utilização do programa. Conclui-se que o conhecimento e a relevância dada às ferramentas de Telessaúde pelos profissionais e seu entorno estão mais associadas a seu uso que as condições estruturais de trabalho

Heartbeat classification system based on neural networks and dimensionality reduction

Abstract Introduction This paper presents a complete approach for the automatic classification of heartbeats to assist experts in the diagnosis of typical arrhythmias, such as right bundle branch block, left bundle branch block, premature ventricular beats, premature atrial beats and paced beats. Methods A pre-processing step was performed on the electrocardiograms (ECG) for baseline removal. Next, a QRS complex detection algorithm was implemented to detect the heartbeats, which contain the primary information that is employed in the classification approach. Next, ECG segmentation was performed, by which a set of features based on the RR interval and the beat waveform morphology were extracted from the ECG signal. The size of the feature vector was reduced by principal component analysis. Finally, the reduced feature vector was employed as the input to an artificial neural network. Results Our approach was tested on the Massachusetts Institute of Technology arrhythmia database. The classification performance on a test set of 18 ECG records of 30 min each achieved an accuracy of 96.97%, a sensitivity of 95.05%, a specificity of 90.88%, a positive predictive value of 95.11%, and a negative predictive value of 92.7%. Conclusion The proposed approach achieved high accuracy for classifying ECG heartbeats and could be used to assist cardiologists in telecardiology services. The main contribution of our classification strategy is in the feature selection step, which reduced classification complexity without major changes in the performance