CAP: Towards PPG Universal Representation Learning with Patient-level Supervision
Photoplethysmography (PPG) plays a central role in wearable health monitoring and clinical decision support. Yet existing approaches to universal PPG representation learning largely focus on signal-level objectives and often overlook patient-level health context, which limits generalization to complex clinical tasks and heterogeneous cohorts. To address this gap, we construct a large-scale paired PPG-EHR multimodal dataset by distilling fragmented medical histories and clinical records into cohesive, patient-level electronic health records (EHR). Building on this resource, we propose Clinical Anchored Pretraining for PPG (CAP). During pretraining, CAP performs cross-modal contrastive alig...
| Authors | Chenyang He, Xinyi Shao, Shun Huang et al. |
|---|---|
| Primary category | eess.SP |
| Published | 13 June 2026 |
| Last updated at source | 13 June 2026 |
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