NEW METHOD EXPLOITING A HYBRID TECHNIQUES FOR FETAL CARDIAC SIGNAL EXTRACTION

Abstract

According to WHO, 2.6 million babies die during pregnancy. Good monitoring during the prenatal period could provide a significant reduction of this mortality rate. This is possible by detection and extraction of the fetal electrocardiogram (FECG). Extraction of that information is complex due to other noise coming from the mother and within the fetus that drowns out the fetal heart signal. However, new technology and improved filtering technique have provided ways to more accurately and efficiently gather various electrical components regarding fetal heart condition. In this paper, we propose a new source separation filtering method exploiting linear and nonlinear filtering techniques. Our method is a non-invasive extraction technique, where the source signal is the cardiac electrical signal acquired by non-invasive electrodes to facilitate the collection of signals and reduce the cost of the acquisition system; it differs from other existing methods in minimizing the number of input signals and the simplicity of its implementation. The fetal heart signal is drowned out by the maternal electrocardiogram (MECG). The problem that arises is the exact knowledge of the MECG signal affecting the chosen measuring electrode, since the MECG is dependent on the position of the electrode and the type of tissue that goes through. Therefore, its knowledge can be made only by a mathematical estimation. A DWT decomposition with adaptive thresholding based on an LMS filter is applied to extract the fetal signal. So first we extract the QRS complex of the FECG and detect the fetal heart rate (FHR).