Classifying multichannel ECG patterns with an adaptive neural network
Senén Barro, Manuel Fernández-Delgado, J.A. Vila-Sobrino, Carlos V. Regueiro, Eduardo Sánchez · IEEE Engineering in Medicine and Biology Magazine · 1998
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.