Multi-task self-supervised learning framework via contrastive restoration for sleep apnea syndrome detection using single-lead ECG

Qi Shen, Guanzheng Liu, Zhiqiong Wang, Xinyao Liu, Junchang Xin

Abstract: Highlights•The potential of single-lead ECG in sleep apnea (SA) detection is explored.•A multi-task self-supervised learning framework is proposed for SA detection.•Quantitative and qualitative experiments verify the effectiveness of the method.