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

Volume

17

Issue

1

fYear

1998

Firstpage

45

Lastpage

55

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;

fLanguage

English

Journal_Title

Engineering in Medicine and Biology Magazine, IEEE

Publisher

ieee

ISSN

0739-5175

Type

jour

DOI

10.1109/51.646221

Filename

646221