Detalhes bibliográficos
| Ano de defesa: |
2017 |
| Autor(a) principal: |
OLIVEIRA jÚNIOR, Alfredo Costa
 |
| Orientador(a): |
BARROS FILHO, Allan Kardec Duailibe
|
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal do Maranhão
|
| Programa de Pós-Graduação: |
PROGRAMA DE PÓS-GRADUAÇÃO EM ENGENHARIA DE ELETRICIDADE/CCET
|
| Departamento: |
DEPARTAMENTO DE ENGENHARIA DA ELETRICIDADE/CCET
|
| País: |
Brasil
|
| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://tedebc.ufma.br:8080/jspui/handle/tede/1293
|
Resumo: |
Atrial fibrilation(AF) is one of the most common cardiac arrhythmias worldwide. Thus, there are ample efforts to implement AF diagnosis systems. The main noninvasive way to assess cardiac health is through electrocardiogram (ECG) signal analysis, which represents the electrical activity of the cardiac muscle, and has characteristic temporal markings: P, Q, R, S and T waves. Some authors use filtering techniques, statistical analysis and even neural networks for detecting AF based on the RR interval, that is given by the temporal difference between the peaks of the R wave. However, analises of the RR interval allows for evaluating changes occurring only in the R wave of the ECG signal, not allowing to assess, for example, variations in the P wave provoked by the AF. In face of that, we propose characterize the ECG signal amplitude aiming at classifying both healthy and AF patients. The ECG signal was analyzed in the proposed methodology through the following statistics: variance, asymmetry, and kurtosis. Herein, we use the MIT-BIH Atrial Fibrillation and MIT-BIH Normal Sinus Rhythm database signals to evaluate AF and normal heartbeat intervals. Our study shown that kurtosis outperfomed variance and asymmetry with respect to sensibility (Se = 100%), specificity (Sp = 88.33%) and accuracy (Ac = 91.33%). The results were expected since kurtosis is a non-Gaussian measure and the ECG signal has sparse distribution. The proposed methodology also requires a lower number of pre-processing stages, and its simplicity allows for implementations in imbedded systems supporting the clinical diagnosis. |
