Theoretical analysis of sequential adaptive processing for fetal electrocardiograms

Fetal electrocardiograms (ECGs) are useful for monitoring fetal health during pregnancy. Previously published results demonstrated that a sequential combination of adaptive linear prediction (LPC), adaptive noise cancellation (ANC), and IIR comb filtering (CF) is an effective strategy to remove maternal interference from fetal ECGs. This paper presents a theory of how LPC-ANC sequential processing is capable to extract fetal signals from noninvasive abdominal measurements. Results are presented to demonstrate that multi-channel adaptive processing is more effective than signal channel processing. Finally, results illustrate that sequential processing followed by single stage of comb filtering is more effective than direct comb filtering.