Pulse-PPG

University of Illinois Urbana-Champaign

PPG / wearable

Filter catalog by Modality:
PPG / Wearable

General Purpose / Multi-task

Filter catalog by Disease / Trait:
General / Foundation

Embedding

Filter catalog by Task Type:
Representation Learning

CNN (1D)

Filter catalog by Architecture:
Convolutional (CNN)

PyTorch

Filter catalog by Framework:
PyTorch

MIT

Filter catalog by License:
Permissive

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Open-source PPG foundation model pretrained directly on real-world, field-collected wearable data rather than clean clinical signals alone, aiming for better generalization to the noise of free-living conditions. Uses a ResNet-based encoder trained with a relative contrastive (RelCon) self-supervised objective, and is directly benchmarked against PaPaGei. Developed at the University of Illinois Urbana-Champaign and published at UbiComp 2025.

memory Specifications

gavel License

MIT

check_small Open source check_small Commercial use OK check_small Modifications allowed Attribution required No share-alike requirement

License for model weights only. Associated code may be licensed seperately, check code source for specific terms.

description Publication

Pulse-PPG: An Open-Source Field-Trained PPG Foundation Model for Wearable Applications Across Lab and Field Settings open_in_new

2025 · original paper

database Training & evaluation data

MOODS Field PPG Dataset

train

Real-world wearable PPG data collected in field settings (used for Pulse-PPG training)

science Capabilities & performance