{"doi":"10.1145/3749494","title":"Pulse-PPG: An Open-Source Field-Trained PPG Foundation Model for Wearable Applications across Lab and Field Settings","abstract":"Photoplethysmography (PPG)-based foundation models are gaining traction due to the widespread use of PPG in biosignal monitoring and their potential to track diverse health indicators. In this paper, we introduce Pulse-PPG, an open-source PPG foundation model trained exclusively on raw PPG data collected over a 100-day field study with 120 participants. Existing open-source PPG foundation models are trained on clinical data, and those trained on field data are closed source, limiting their applicability in real-world settings. Extensive evaluations demonstrate that Pulse-PPG, trained on uncurated field data, exhibits superior generalization and performance across clinical and mobile health applications in both lab and field settings, when compared with state-of-the-art PPG foundation models trained on clinical data. Exposure to real-world variability in field-collected PPG data enables Pulse-PPG to learn more robust representations. Furthermore, pre-training Pulse-PPG on field data outperforms its own pre-training on clinical data in many tasks, reinforcing the importance of training on real-world datasets. To encourage further advancements in robust PPG modeling, we have open-sourced*our Pulse-PPG model, providing researchers with a valuable resource for developing the next generation of task-specific PPG-based models.","journal":"Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies","year":2025,"id":513561,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":10,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.931,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1349140,"name":"Maxwell A. Xu","orcid":"0000-0002-1017-3840","position":1,"is_corresponding":false},{"id":1375334,"name":"Wanting Mao","orcid":null,"position":2,"is_corresponding":false},{"id":1299575,"name":"Sameer Neupane","orcid":"0000-0002-5739-2362","position":3,"is_corresponding":false},{"id":322852,"name":"James M. Rehg","orcid":"0000-0003-1793-5462","position":4,"is_corresponding":false},{"id":372093,"name":"Santosh Kumar","orcid":"0000-0002-9273-0291","position":5,"is_corresponding":false},{"id":1325495,"name":"Mithun Saha","orcid":"0000-0003-1510-4307","position":0,"is_corresponding":true}],"reference_count":69,"raw_metadata":null,"created_at":"2026-07-19T02:48:17.908238Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}