Fully automatic electrocardiogram classification system based on generative adversarial network with auxiliary classifier

A generative adversarial network (GAN) based fully automatic electrocardiogram (ECG) arrhythmia classification system with high performance is presented in this paper. The generator (G) in our GAN is designed to generate various coupling matrix inputs conditioned on different arrhythmia classes for data augmentation. Our designed discriminator (D) is trained on both real and generated ECG coupling matrix inputs, and is extracted as an arrhythmia...