Extended Barros´s extraction algorithm with its application in fetal ECG extraction

The extraction of fetal electrocardiogram (ECG) from maternal skin electrode measurements is an open problem in recent decades. Since the problem can be modelled from the perspective of blind source separation (BSS), almost all the BSS algorithms can be used to separate the fetal ECG. However, since separating all the sources from a large number of sensor signals is not necessary, blind source extraction (BSE) methods maybe a better choice. Until now the only efficient BSE algorithm that can be used in this problem seems to be the Barros´s algorithm. But it requires a priori knowledge about the sources´ autocorrelation information, which limits its application to extracting some completely unknown sources. This paper extends the algorithm, and proposes a novel preprocessing, which can extract completely unknown sources that have autocorrelation properties. Simulations on real-world fetal ECG data shows the new algorithm with the preprocessing can achieve satisfying results