Deep Convolutional Neural Network Model For Classification Of Atrial Fibrillation

Abstract

Atrial fibrillation is a very common heart pathology, which is usually detected from electrocardiogram (ECG). This article presents recognition of atrial fibrillation in ECG using deep convolutional neural network. Data used for training the network includes physiological ECG, atrial fibrillation and nine other pathologies. The detection is performed by algorithm in Python language and is being assessed by accuracy and F1 measure.