From the start, major efforts were devoted to advancing the technology used to capture and process electrophysiological signals. The fellowship led to several key achievements:
• Better detection of the fetal heartbeat: New algorithms were developed to reliably extract the fetal ECG (electrocardiogram) from abdominal recordings, even when using textile electrodes designed to be comfortable, wearable, and completely non-invasive.
• Detailed characterization of the heartbeat: For the first time, techniques were designed for extracting single-cycle features from the fetal ECG, providing richer information about the development and the functioning of the baby’s.
• Monitoring contractions: Innovative algorithms were created to analyze uterine electrical signals and automatically detect contractions, offering a powerful tool for monitoring preterm birth risks.
• Understanding maternal–fetal interactions: Using advanced statistical models, the project demonstrated that maternal breathing plays an unexpectedly important role in shaping the cardiovascular coupling between mother and fetus.
• Early detection of anomalies: Most importantly, the project showed that differences in maternal–fetal coupling are already visible in the second trimester in fetuses affected by congenital heart disease. This finding suggests that coupling metrics could enable earlier and more accurate diagnosis of fetal pathologies, complementing conventional screening tools.
Although the collection of new multimodal datasets was limited, the project successfully used clinical datasets from partners, public resources, and pre-existing recordings from the host institution. This ensured that the objectives were achieved and, in some cases, exceeded expectations.
The results were widely disseminated through presentations at leading international conferences, multiple journal submissions, and outreach activities targeting both scientific and non-specialist audiences. Notably, a dedicated special session on maternal–fetal monitoring will be organized at the IEEE Biomedical and Health Informatics Conference (BHI) in 2025, further boosting the project’s visibility and impact.