A Novel Approch for Fetal Ecg Using Adaptive Filter Algorithm

Abstract

Fetal Electrocardiogram (FECG) signals, non-invasively taken from the Abdominal Electrocardiogram (AECG) of a pregnant woman is an efficient diagnostic tool for evaluating the health status of foetus. Clinically significant information in the Fetal Electrocardiogram signal is often masked by Maternal Electrocardiogram (MECG) considered as the most predominant interference, power line interference, and maternal Electromyogram (EMG), baseline wander etc. Fetal Electrocardiogram signal features may not be readily comprehensible by the visual or auditory systems of a human. Therefore Fetal Electrocardiogram should be extracted from composite Abdominal Electrocardiogram for clinical diagnosis. There are many powerful and well advanced methods for this purpose. A methodological study has been carried out to show the effectiveness of various methods which helps in understanding of Fetal ECG signal and its analysis procedures by providing valuable information and we have proposed a method to find the size of fetal for every month. We have finded the edges of fetal using edge detection algorithm for forth month and compared with fifth month by using adaptive filter algorithm. This is done for every advanced month of fetal.