Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/44089
Title: Improving an automatic arrhythmias recogniser based in ECG signals
Authors: Corsino, Jorge
Travieso, Carlos M. 
Alonso, Jesús B. 
Ferrer, Miguel A. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Wavelet transform, Automatic recognition of arrhythmias, Electrocardiography, Neural network, Principal component analysis
Issue Date: 2008
Journal: BIOSIGNALS 2008 - Proceedings of the 1st International Conference on Bio-inspired Systems and Signal Processing
Conference: 1st International Conference on Bio-Inspired Systems and Signal Processing 
BIOSIGNALS 2008 - 1st International Conference on Bio-inspired Systems and Signal Processing 
Abstract: 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
Source: BIOSIGNALS 2008 - Proceedings of the 1st International Conference on Bio-inspired Systems and Signal Processing,v. 2, p. 453-457
Appears in Collections:Actas de congresos
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