Fetal ECG

Noninvasive fetal electrocardiography (fECG) aims to extract the fetal heartbeat signal from maternal abdominal recordings to monitor fetal heart health. Current research heavily utilizes advanced signal processing techniques, including deep learning models like CycleGANs and anatomically-constrained image registration algorithms, to overcome challenges posed by signal overlap and noise. These improvements in fECG extraction are crucial for enhancing prenatal diagnosis of fetal heart conditions, potentially reducing infant mortality and improving neonatal outcomes by enabling earlier and more accurate assessments of fetal cardiac function.