Evolutionary Training of a Neurofuzzy Network for Detection of P Wave of the ECG

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Venue:
ICCIMA '99 Proceedings of the 3rd International Conference on Computational Intelligence and Multimedia Applications
Year:
1999

Citing 0
Cited 4

Comparison of FCM, PCA and WT techniques for classification ECG arrhythmias using artificial neural network

Expert Systems with Applications: An International Journal
Intelligent classification of electrocardiogram (ECG) signal using extended Kalman Filter (EKF) based neuro fuzzy system

Computer Methods and Programs in Biomedicine
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Abstract

In this work it is presented a neurofuzzy network that is applied to the detection of a specific wave of the electrocardiographic signal. The network was trained using genetic algorithms, using a software package publicly available in the Internet. The training procedure, its parameters and details of the application are presented. Results suggest that this kind of network is suitable for the identification of patterns in unidimensional time-varying signals.