Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/44089
Título: Improving an automatic arrhythmias recogniser based in ECG signals
Autores/as: Corsino, Jorge
Travieso, Carlos M. 
Alonso, Jesús B. 
Ferrer, Miguel A. 
Clasificación UNESCO: 3307 Tecnología electrónica
Palabras clave: Wavelet transform, Automatic recognition of arrhythmias, Electrocardiography, Neural network, Principal component analysis
Fecha de publicación: 2008
Publicación seriada: BIOSIGNALS 2008 - Proceedings of the 1st International Conference on Bio-inspired Systems and Signal Processing
Conferencia: 1st International Conference on Bio-Inspired Systems and Signal Processing 
BIOSIGNALS 2008 - 1st International Conference on Bio-inspired Systems and Signal Processing 
Resumen: In the present work, we have developed and improved a tool for the automatic arrhythmias detection, based on neural network with the "more-voted" algorithm. Arrhythmia Database MIT has been used in the work in order to detect eight different states, seven are pathologies and one is normal. The unions of different blocks and its optimization have found an improvement of success rates. In particular, we have used wavelet transform in order to characterize the patron wave of electrocardiogram (ECG), and principal components analysis in order to improve the discrimination of the coefficients. Finally, a neural network with more-voted method has been applied.
URI: http://hdl.handle.net/10553/44089
ISBN: 9789898111180
Fuente: BIOSIGNALS 2008 - Proceedings of the 1st International Conference on Bio-inspired Systems and Signal Processing,v. 2, p. 453-457
Colección:Actas de congresos
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