Title :
Classifying multichannel ECG patterns with an adaptive neural network
Author :
Barro, S. ; Fernández-Delgado, M. ; Vila-Sobrino, J.A. ; Regueiro, C.V. ; Sánchez, E.
Author_Institution :
Dept. of Electron. & Comput., Santiago de Compostela Univ., Spain
Abstract :
In this article the authors describe the application of a new artificial neural network model aimed at the morphological classification of heartbeats detected on a multichannel ECG signal. They emphasize the special characteristics of the algorithm as an adaptive classifier with the capacity to dynamically self-organize its response to the characteristics of the ECG input signal. They also present evaluation results based on traces from the MIT-BIH arrhythmia database
Keywords :
adaptive signal processing; electrocardiography; medical signal processing; neural nets; ECG input signal; MIT-BIH arrhythmia database; adaptive neural network; algorithm characteristics; dynamically self-organized response; electrodiagnostics; heartbeats; morphological classification; multichannel ECG patterns classification; Adaptive signal detection; Adaptive systems; Artificial neural networks; Databases; Electrocardiography; Morphology; Neural networks; Noise generators; Noise level; Signal processing;
Journal_Title :
Engineering in Medicine and Biology Magazine, IEEE
