in this paper, we propose a technique of artificial intelligence called adaptive neuro fuzzy inference system (anfis) for canceling maternal electrocardiogram (mecg) in fetal electrocardiogram extraction (fecg).this technique is used to estimate the mecg present in the abdominal signal of a pregnant woman. the fecg is then extracted by subtracting the estimated mecg from the abdominal signal. p...

Fetal ECG extraction has an important role in the medical diagnosis during pregnancy. This problem can be modeled from the approach of blind source extraction. The mathematical modeling of fetal ECG extraction using ICA algorithm is described in this paper. It also proposes an efficient BSS method (FCOMBI) for the extraction of fetal ECG. This algorithm combines the strengths of non-Gaussianity...

Electrocardiogram (ECG) is a valuable technique that has been in use for over a century. The analysis of fetal ECG signal has always been an interesting topic in the field of signal processing. The presence of noises in the ECG signal causes distortion in the signal morphology. While analyzing the fetal ECG this distortion of the signal is much more severe as the fetal ECG is much weaker than t...

Background: Extraction of Fetal ECG signal from non-invasive abdominal ECG signal is an important clinical application. Fetal ECG signal provides significant and valuable information about the fetal heart growth and health condition. Objective: Abdominal signals are usually corrupted by high amplitude maternal ECG signals and often found superimposed with the Fetal ECG signal. Suppression of ma...

Analysis of the fetal heart rate during pregnancy is essential for monitoring proper development fetus. Current techniques lack accuracy in and features acquisition, resulting diagnostic medical issues. The challenge lies extraction ECG from mother pregnancy. This approach has advantage being a reliable non-invasive technique. In present paper, wavelet/multiwavelet method proposed to perfectly ...