Enhanced Atrial Fibrillation (Af) Detection Via Data Augmentation With Diffusion Model Publisher



Vashagh A¹ ; Akhoondkazemi A¹ ; Zahabi SJ¹ ; Shafie D² Show Affiliations
Source: 2023 13th International Conference on Computer and Knowledge Engineering, ICCKE 2023 Published:2023

Abstract

Atrial Fibrillation (AF) is the most common type of cardiac arrhythmia, posing significant health risks such as strokes and cardiac failure. Deep learning methods have been employed to automatically diagnose AF from electrocardiogram (ECG) signals. In this study, transforming the ECG signal into two-dimensional Poincare plots, we explore the application of diffusion model in the augmentation of AF samples to improve the performance of AF detection via deep learning. In this regard, we compare the performance of diffusion model and generative adversarial network (GAN). Our results suggest that diffusion model can potentially generate more satisfactory samples in terms of both the FID score and the downstream classification task. © 2023 IEEE.