Desenvolvimento de um software para análise de eletrocardiogramas utilizando dispositivos móveis
According to the mortality indicators of Interagency Network of Health Information (RIPSA) 2010, about 30% of deaths are related to cardiovascular diseases. Another problem to health is the lack of qualified professionals in the area of heart disease. By checking this data, there is a vast area for...
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| Format: | master thesis |
| Status: | Published version |
| Publication Date: | 2015 |
| Country: | Brasil |
| Institution: | Universidade Federal do Triangulo Mineiro (UFTM) |
| Repository: | Biblioteca Digital de Teses e Dissertações da UFTM |
| Language: | Portuguese |
| OAI Identifier: | oai:bdtd.uftm.edu.br:tede/207 |
| Online Access: | http://bdtd.uftm.edu.br/handle/tede/207 |
| Access Level: | Open access |
| Keyword: | Programação Java Aplicativo Android Processamento de imagens Java programing Android application Image processing Processamento Gráfico |
| Summary: | According to the mortality indicators of Interagency Network of Health Information (RIPSA) 2010, about 30% of deaths are related to cardiovascular diseases. Another problem to health is the lack of qualified professionals in the area of heart disease. By checking this data, there is a vast area for studies in an attempt to help to change this reality. In this context, the proposed study aims to develop an application that can scan a portion of an electrocardiogram and store it. In addition, it is intended to provide means to facilitate rapid and varied sharing of these scanned images, then perform the treatment of the captured image in order to isolate only the signal of the electrocardiogram leaving it ready for analysis and study of possible diseases that involve the heart. The application also performs compression using FFT and offers a basic manual with some heart diseases for consultation. The software has been developed and designed for mobile devices that use the Android operating system. In this context, for the treatment of the scanned image and isolation of the ECG signal, the following algorithms have been used: negative, threshold, blob filtering, extract and refine biggest blob. Besides, in order to compress and restore the ECG, the discrete Fourier Transform and the inverse discrete Fourier Transform were used. The results showed that it is possible to implement all these features in a mobile device with Android API 14 without performance problems and with quality. The ECG signal was successfully isolated, transmitted and restored. Thus, there is a possibility for health professionals to exchange information and experiences quickly and conveniently, and also to identify serious diseases in patients. |
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