AnyPPG: An ECG-Guided PPG Foundation Model Trained on Over 100,000 Hours of Recordings for Holistic Health Profiling

Summary

AnyPPG pretrains a PPG encoder (Net1D/ResNet-style, 512-dim) using a CLIP-style cross-modal contrastive objective against a frozen ECG foundation model (ECGFounder) instead of PPG-only self-supervised learning. Pretraining data is 109,909 hours / 58,796 subjects of synchronized PPG+ECG from five clinical sources (MC-MED, PulseDB [MIMIC+VitalDB derived], MESA, HSP, CFS) — largely ICU and sleep-lab, not wearable. At inference only PPG is needed (ECG branch is pretraining scaffolding).