Design and Implementation of Least Mean Square Adaptive Filter on Fetal Electrocardiography

This paper demonstrates the Least Mean Square (LMS) adaptive filter for adaptive noise (interference) removal. A measured signal contains an unknown signal of interest and an interference signal. The goal is to design an LMS based adaptive noise canceller that adaptively removes the maternal heartbeat signal from the fetal electrocardiogram signal. This Least Mean Square based adaptive filter will remove the interference signal from the measured signal by using a reference signal. The reference Signal used is highly correlated with the interference signal. The filtration is achieved by designing a Least Mean Square adaptive filter with a specific order and step size that will ensure the adaptation of the filter to converge after few seconds of adaptation.