CLEP-GAN: an innovative approach to subject-independent ECG reconstruction from PPG signals

Our method produces synthetic ECG-PPG pairs with RR interval distributions closely aligned with their real counterparts and shows strong potential to simulate diverse rhythms such as regular sinus rhythm (RSR), sinus arrhythmia (SA), and atrial fibrillation (AFib). Furthermore, CLEP-GAN demonstrates robust performance on both synthetic and real datasets, achieving near-perfect reconstruction in synthetic settings and competitive results on real data. These findings highlight CLEP-GAN's promise for reliable, non-invasive ECG monitoring in clinical applications.