IEEE Rev Biomed Eng. 2020;13:51-73. doi: 10.1109/RBME.2019.2938061. Epub 2019 Aug 29.
Fetal electrocardiography (fECG) is a promising alternative to cardiotocography continuous fetal monitoring. Robust extraction of the fetal signal from the abdominal mixture of maternal and fetal electrocardiograms presents the greatest challenge to effective fECG monitoring. This is mainly due to the low amplitude of the fetal versus maternal electrocardiogram and to the non-stationarity of the recorded signals. In this review, we highlight key developments in advanced signal processing algorithms for non-invasive fECG extraction and the available open access resources (databases and source code). In particular, we highlight the advantages and limitations of these algorithms as well as key parameters that must be set to ensure their optimal performance. Improving or combining the current or developing new advanced signal processing methods may enable morphological analysis of the fetal electrocardiogram, which today is only possible using the invasive scalp electrocardiography method.
胎儿心电图（fECG）是一种有前途的替代胎心监护的方法。从腹部的母体和胎儿心电图混合物中稳健地提取胎儿信号是有效 fECG 监测的最大挑战。这主要是由于胎儿心电图相对于母体心电图的幅度较低，以及记录信号的非平稳性。在本综述中，我们重点介绍了用于非侵入性 fECG 提取的先进信号处理算法的关键进展以及可用的开放访问资源（数据库和源代码）。特别是，我们强调了这些算法的优缺点以及必须设置的关键参数，以确保它们的最佳性能。改进或组合当前或开发新的先进信号处理方法可能会使胎儿心电图的形态分析成为可能，而这种分析目前只能使用有创头皮心电图方法实现。
