|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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