Fetal electrocardiogram (fECG) monitoring is a technique for obtaining important information about the condition of the fetus during pregnancy and labour by measuring electrical signals generated by the fetal heart as measured from multi-channel potential recordings on the mother body surface. It is shown in this paper that the fetal ECG can be reconstructed by means of higher order statistical...

non-invasive fetal electrocardiogram (FECG) signal extraction from signals recorded at abdominal area of mother is a challenging problem for the biomedical and signal processing communities. In this paper, we improve the FECG extraction approaches which consist to find the relation-ships between the cardiac potentials generated at the heart level of mother and the potentials recorded on the abd...

Fetal Electrocardiogram Extraction (FECG) identifies the congenital heart problems at the earlier stage. The major problem in the non invasive procedure is the extraction of FECG from Maternal ECG (MECG) and many interferences. The proposed methods (i) Combination of Adaptive Neuro Fuzzy Inference (ANFIS) and Fractional spline wavelet (ii) Combination of Fractional spline wavelet and ANFIS (iii...

This paper evaluates the performance of some major Independent Component Analysis (ICA) algorithms like Hyv ̈arinen’s fixed point algorithm, Pearson based ICA algorithm and OGWE (Optimized Generalized Weighted Estimator) ICA algorithm in a biomedical blind source separation problem. Independent signals representing Fetal ECG (FECG) and Maternal ECG (MECG) generated and then mixed linearly to sim...

Interference of power line (PLI) (fundamental frequency and its harmonics) is usually present in biopotential measurements. Despite all countermeasures, the PLI still corrupts physiological signals, for example, electromyograms (EMG), electroencephalograms (EEG), and electrocardiograms (ECG). When analyzing the fetal ECG (fECG) recorded on the maternal abdomen, the PLI represents a particular s...

This paper evaluates the performance of some major ICA algorithms like Cardoso’s Joint Approximate Diagonalization of Eigen matrices (JADE), Bell and Sejnowski’s Infomax algorithm and Comon’s algorithm in a biomedical blind source separation problem. Independent signals representing Fetal ECG (FECG) and Maternal ECG (MECG) generated and then mixed linearly to simulate a recording of electrocard...

Fetal electrocardiogram (FECG) extraction is a vital issue in biomedical signal processing and analysis. A promising approach is blind (semi-blind) source extraction. In this paper, we develop an objective function for extraction of temporally correlated sources. The objective function is based on the non-Gaussianity and the autocorrelations of source signals, and it contains the well-known mea...

The aim of this paper is to model the algorithm for Fetal ECG (FECG) extraction from composite abdominal ECG (AECG) using VHDL (Very High Speed Integrated Circuit Hardware Description Language) for FPGA (Field Programmable Gate Array) implementation. Artificial Neural Network that provides efficient and effective ways of separating FECG signal from composite AECG signal has been designed. The p...

This article deals with utilization of the combination of the fuzzy system and artificial intelligence techniques, called the Adaptive Neuro Fuzzy Inference System ANFIS, with the aim to refine the diagnostic quality of the abdominal fetal electrocardiogram FECG. Within the scope of the experiments carried out and based on the ANFIS structure the authors created a complex system for removing th...