Universal 12-lead ECG representation for signal denoising and cardiovascular disease detection by fusing generative and contrastive learning

Jiguang Shi, Wenhan Liu, Huaicheng Zhang, Zhoutong Li, Sheng Chang, Hao Wang, Jin He, Qijun Huang

Abstract: Highlights•Develop a self-supervised learning model (GCL) to learn representations from unlabeled ECG signals.•GCL combines the advantages of generative and contrastive learning.•Suitable for downstream classification and denoising tasks.•GCL is deployed on a heterogeneous SoC for designing portable cardiovascular disease detection devices.