Adaptive signal processing techniques for extracting fetal electrocardiograms from noninvasive measurements

In clinical medicine fetal electrocardiograms (ECGs) are useful for monitoring fetal health during pregnancy. This research investigates a variety of adaptive filtering techniques to remove maternal interference from fetal ECGs and to determine which techniques are most effective under varying circumstances. Experimental results suggest that a sequential combination of adaptive linear prediction coding (LPC), adaptive noise cancellation (ANC), and IIR comb filtering provides an effective strategy to remove maternal interference from fetal ECGs. It is shown how digital comb filters can be used effectively to separate maternal and fetal signal components based on distinct spectral content of the two signals.