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Diagnóstico de doença cardíaca a partir do eletrocardiograma

Diagnóstico de doença cardíaca a partir do eletrocardiograma

Shadi Obaid / Umar Alqasemi

55,87 €
IVA incluido
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Editorial:
KS OmniScriptum Publishing
Año de edición:
2024
Materia
Informática: cuestiones generales
ISBN:
9786207595969
55,87 €
IVA incluido
Disponible

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Sobre IBD

A classificação dos sinais de ECG de forma manual ou tradicional é uma área que pode ser melhorada através de um sistema de classificação automatizado dos sinais de ECG. Neste trabalho, é introduzido um sistema de software de diagnóstico assistido por computador (CAD) melhorado para a classificação automática de sinais de ECG cardíaco. Para efeitos deste estudo, foram utilizados 480 sinais de ECG da base de dados de arritmias do MIT-BIH; esses sinais incluem 96 sinais de ECG normais e 384 sinais de ECG anómalos pertencentes a quatro tipos de anomalias cardíacas, nomeadamente, acoplamento ventricular, taquicardia ventricular, bigeminia ventricular e fibrilhação ventricular, tendo cada um desses tipos 96 sinais de ECG. Em seguida, procedeu-se à reamostragem de todos os sinais a 360 amostras por segundo, com exceção dos sinais de FV, que foram reamostrados a 250 amostras por segundo. Depois disso, foi aplicado um processo iterativo de extração de características com a ajuda da aplicação Classification Learner App existente no MATLAB.

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