Recently, non-invasive techniques to measure the fetal electrocardiogram (FECG) signal have given very promising results. However, the important question of the number and the location of the external sensors has been often discarded. In this paper, an electrode-array approach is proposed; it is combined with a sensor selection algorithm using a mutual information criterion. The sensor selectio...

Fetal electrocardiogram (FECG) extraction is very important procedure for fetal health assessment. In this article, we propose a fast one-unit independent component analysis with reference (ICA-R) that is suitable to extract the FECG. Most previous ICA-R algorithms only focused on how to optimize the cost function of the ICA-R and payed little attention to the improvement of cost function. They...

In biomedical engineering, to extract the fetal electrocardiogram (FECG) exactly is a significant and challenging research topic, and so it has been a hot field in biomedical research. Now, a variety of different methods have been proposed to address this problem. From the perspective of blind signal processing, FECG extraction can be modeled as Blind source separation (BSS). In this paper, we ...

Fetal electrocardiogram (Fetal ECG) extraction is an interesting as well as a difficult problem in signal processing. The original FECG signal is nevertheless very complex and severely contaminated by external disturbances or noises. Identification of these cases during early pregnancy reduces risks by timely treatment or planned delivery. This paper presents simulation results of fetal ECG sig...

Fetal electrocardiogram (FECG) signals contain important information about the conditions of fetus during pregnancy. Currently, pure FECG can only be obtained through an invasive acquisition process, which is life threatening to both mother and fetus. In this study, single-channel ECG from mother’s abdomen are analyzed with aim extracting clean waveform. This a challenging task due very low amp...

The detection of a fetal electrocardiogram (FECG) is described to be a so-called inverse problem. A geometric interpretation of such a problem is presented. It can be solved by determining the weights to be used in one or more weighted sums of measurement signals. A novel method is presented to determine these weights. Theoretical and experimental evidence is given that this method has the foll...

Abstract Congenital heart disease (CHD) is a leading cause of infant death. To diagnose CHD, recordings from abdominal fetal electrocardiograms (fECG) can be used as non-invasive tool. However, it challenging to extract the signal fECG partly due lack data combining with ground truth for signal, which obtained by using scalp electrode during delivery. In this study, we present computational mod...

Fetal heart rate (FHR) monitoring is currently the primary methodology for antenatal determination of fetal well-being. Currently, the FHR can be detected with ultrasonography, but the additional information from fetal electrocardiogram (FECG) is only available via an invasive scalp electrode. A cost effective noninvasive monitoring through standard ECG electrodes could be used on nearly every ...

In this study we present a noninvasive method that enables the investigation of the fetal heart rate (FHR) fluctuations. The objective was to design a quantitative measurement to assess the fetal autonomic nervous system and to investigate its development as a function of the gestational age. Our Medical Physics group has developed a complex algorithm for online beat-to-beat detection of the fe...

Fetal electrocardiograms (FECG) contain important indications about the health and condition of the fetus. In this respect, it is crucial to apply a robust algorithm to ECG data for extraction of the FECG signal. Most of the independent component analysis (ICA) algorithms used for this purpose rely on simple statistical models. Such algorithms can fail to separate desired signals when the assum...