Signal to Image to Classification: Transfer Learning for ECG

Abstract

Transfer learning offers a potentially valuable tool for detecting a pathological electrocardiogram (ECG) trace. Here, four separate methods of generating an image from a single ECG trace are presented. Transfer learning is used to train three deep neural networks for classification of these images into healthy or pathological categories. The performance of the three pretrained networks is compared.