Fetal Electrocardiogram Analysis Using Adaptive filters

It is critical to obtain information about the fetus early in pregnancy to avert stillbirth. Medical personnel use Cardiotocography (CTG) to monitor the fetus's health in the hospital, however, it is not possible to record continuous long-duration signals using this method. As a result, constant and long-term monitoring of fetal electrocardiogram[1] signals is required to determine the health condition utilizing portable instruments. The invasive approach is superior to an invasive method for measuring ECG signals. To retrieve FECG encoded in the mother ECG, compact electronics and advanced signal processing techniques were required. Because the Fetal Heartbeat from the abdomen is frequently contaminated or interfered with by the Maternal Heartbeat, which is essentially noise. As a result, an attempt is made to separate the Fetal Heartbeat from the interfering Maternal Heartbeat in this case. The Adaptive [2] Noise Canceller (ANC) is used to remove the signal's noise content. Different adaptive filtering schemes, such as Single Input Single Output (SISO) on ANC, where adaptive algorithms such as least mean squares (LMS), Normalized least mean squares (NLMS), and leaky least mean [7] squares (L-LMS) are implemented in MATLAB and simulation results show the extracted FECG noise-free signal.