{"doi":"10.1109/tbme.2025.3623609","title":"FOSTER: A Comprehensive Pipeline for Transabdominal Fetal Pulse Oximetry Validated in a Large Animal Model of Pregnancy","abstract":"OBJECTIVE: Transabdominal fetal pulse oximetry (TFO) has the potential to supplement present intrapartum fetal monitoring approaches, which cannot accurately detect fetuses at risk of birth asphyxia. However, non-invasive measurement of fetal oxygen saturation (fSpO$_{2}$) is challenging due to dominant maternal tissue signals. We present methods to overcome such challenges, enabling robust and continuous fSpO$_{2}$ measurement. METHODS: We introduce FOSTER (Fetal Oxygen SaTuration EstimatoR), a comprehensive pipeline that combines novel signal processing and machine learning techniques to process photoplethysmogram (PPG) signals and estimate continuous fSpO$_{2}$. Using controlled desaturation experiments in pregnant ewes, we evaluate FOSTER's performance with both mixed maternal-fetal signals and isolated fetal components. RESULTS: Processing isolated fetal signals improves estimation accuracy with respect to arterial blood oxygen saturation (SaO$_{2}$), showing improvements of 13.7% in mean absolute error (MAE) and 10.5% in Pearson correlation coefficient relative to using mixed TFO signals alone. A dual-branch neural network, processing mixed and isolated PPG signals simultaneously, achieves additional improvements of 6.3% in MAE and 4.1% in Pearson correlation compared to using isolated fetal signals alone. CONCLUSION: The FOSTER pipeline demonstrates significant improvements in continuous fSpO$_{2}$ estimation accuracy through advanced signal processing and a dual-branch architecture, establishing a foundation for reliable fSpO$_{2}$ monitoring. SIGNIFICANCE: This work represents an important innovative step toward accurate, continuous, and non-invasive monitoring of fetal oxygenation. The validated methods in animal studies establish a foundation for advancing the development of fetal monitoring systems, offering new possibilities for improved maternal-fetal care.","journal":"IEEE Transactions on Biomedical Engineering","year":2025,"id":578793,"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":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9574,"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":819005,"name":"Mahya Saffarpour","orcid":"0000-0002-6643-259X","position":1,"is_corresponding":false},{"id":808294,"name":"Weitai Qian","orcid":"0000-0001-9615-2460","position":2,"is_corresponding":false},{"id":1445706,"name":"Rishad Joarder","orcid":"0000-0002-7012-5162","position":3,"is_corresponding":false},{"id":808293,"name":"Kourosh Vali","orcid":"0000-0002-7165-6715","position":4,"is_corresponding":false},{"id":808297,"name":"Soheil Ghiasi","orcid":"0000-0002-1036-791X","position":5,"is_corresponding":false},{"id":808292,"name":"Begum Kasap","orcid":"0000-0001-5894-2883","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-19T02:58:24.957414Z","pmid":"41124068","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":[]}