AnyPPG: An ECG-Guided PPG Foundation Model Trained on Over 100,000 Hours of Recordings for Holistic Health Profiling
Guangkun Nie, Xiaocheng Fang, Gongzheng Tang, Yujie Xiao, Jun Li, Bo Liu, Hongyan Li, Shenda Hong

TL;DR
AnyPPG is a large-scale, ECG-guided PPG foundation model that uncovers broad health profiling capabilities of PPG signals, demonstrating significant potential for holistic disease detection across numerous health conditions.
Contribution
This work introduces AnyPPG, the first PPG foundation model trained on over 100,000 hours of synchronized ECG data, enabling extensive health phenotype analysis beyond cardiovascular applications.
Findings
Achieved state-of-the-art performance on 13 out of 15 downstream tasks.
Demonstrated discriminative capability for 307 phenotypes, including non-circulatory diseases.
Revealed PPG signals encode rich health information beyond traditional cardiovascular metrics.
Abstract
Photoplethysmography (PPG) is widely used as a non-invasive and accessible modality for continuous health monitoring. However, despite being a peripheral hemodynamic signal intrinsically coupled with systemic circulation, existing research has largely confined its scope to a narrow range of cardiovascular tasks, leaving a fundamental question underexplored: to what extent can PPG support holistic health profiling beyond traditional cardiovascular applications? To answer this question, we present AnyPPG, a foundation model-based framework designed to reveal the broader health-profiling potential of PPG. To ensure reliable performance for this investigation, AnyPPG is pretrained with ECG guidance on the most diverse PPG corpus with synchronized ECG to date, comprising over 100,000 hours of recordings from six large-scale data sources. This pretraining yields robust and physiologically…
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Taxonomy
TopicsNon-Invasive Vital Sign Monitoring · ECG Monitoring and Analysis · Optical Imaging and Spectroscopy Techniques
