Abstract
Non-invasive fetal electrocardiography (NIFECG), an emerging technology for fetal health monitoring, has garnered significant attention in recent years. It is considered a promising alternative to traditional Doppler ultrasound methods and has the potential to become the standard approach for fetal monitoring. This paper provides a comprehensive review of the latest advancements in NIFECG technology, including signal acquisition, signal preprocessing, fetal electrocardiogram extraction, and fetal cardiac anomaly classification. Furthermore, the characteristics and limitations of existing NIFECG datasets are analyzed, and improvement suggestions are proposed. Future research directions for NIFECG technology are discussed, with a particular focus on the potential applications of deep learning techniques, multimodal data fusion, and remote monitoring systems. This review offers references and support for advancing the development and application of NIFECG monitoring technology.