The fetal electrocardiogram contains within it, information regarding the health of the fetus. Currently, fetal ECG is recorded directly from the scalp of the baby during labour. However, it has been shown that fetal ECG can also be measured using surface electrodes attached to a pregnant mother's abdomen. The advantage of this method lies in the fact that fetal ECG can be measured noninvasively before the onset of labour. The difficulty lies in isolating the fetal ECG from extraneous signals that are simultaneously recorded with it. Several signal processing methodologies have been put forth in order to extract the fetal ECG component from a mixture of signals. Two recent techniques that have been put forth include a scheme that has previously been used to nonlinearly reduce noise in deterministically chaotic noise and the other uses a blind source separation technique called independent component analysis. In this thesis, we describe the significance of the fetal electrocardiogram as a diagnostic tool in medicine, a brief overview of the theory behind the nonlinear noise reduction technique and blind source separation, and results from having processed synthetic and real data using both techniques. We find that although the noise reduction technique performs adequately, the blind source separation process performs faster and more robustly against similar data. The two techniques can be used in tandem to arrive at an approximate fetal ECG signal, which can be further analyzed by calculating, for example, the fetal heart rate. / Thesis / Master of Engineering (ME)

Les malformations cardiaques congénitales sont la première cause de décès liés à une anomalie congénitale. L’´electrocardiogramme du fœtus (ECGf), qui est censé contenir beaucoup plus d’informations par rapport aux méthodes échographiques conventionnelles, peut ˆêtre mesuré´e par des électrodes sur l’abdomen de la mère. Cependant, il est tr`es faible et mélangé avec plusieurs sources de bruit et interférence y compris l’ECG de la mère (ECGm) dont le niveau est très fort. Dans les études précédentes, plusieurs méthodes ont été proposées pour l’extraction de l’ECGf à partir des signaux enregistrés par des électrodes placées à la surface du corps de la mère. Cependant, ces méthodes nécessitent un nombre de capteurs important, et s’avèrent inefficaces avec un ou deux capteurs. Dans cette étude trois approches innovantes reposant sur une paramétrisation algébrique, statistique ou par variables d’état sont proposées. Ces trois méthodes mettent en œuvre des modélisations différentes de la quasi-périodicité du signal cardiaque. Dans la première approche, le signal cardiaque et sa variabilité sont modélisés par un filtre de Kalman. Dans la seconde approche, le signal est découpé en fenêtres selon les battements, et l’empilage constitue un tenseur dont on cherchera la décomposition. Dans la troisième approche, le signal n’est pas modélisé directement, mais il est considéré comme un processus Gaussien, caractérisé par ses statistiques à l’ordre deux. Dans les différentes modèles, contrairement aux études précédentes, l’ECGm et le (ou les) ECGf sont modélisés explicitement. Les performances des méthodes proposées, qui utilisent un nombre minimum de capteurs, sont évaluées sur des données synthétiques et des enregistrements réels, y compris les signaux cardiaques des fœtus jumeaux. / Congenital heart defects are the leading cause of birth defect-related deaths. The fetal electrocardiogram (fECG), which is believed to contain much more information as compared with conventional sonographic methods, can be measured by placing electrodes on the mother’s abdomen. However, it has very low power and is mixed with several sources of noise and interference, including the strong maternal ECG (mECG). In previous studies, several methods have been proposed for the extraction of fECG signals recorded from the maternal body surface. However, these methods require a large number of sensors, and are ineffective with only one or two sensors. In this study, state modeling, statistical and deterministic approaches are proposed for capturing weak traces of fetal cardiac signals. These three methods implement different models of the quasi-periodicity of the cardiac signal. In the first approach, the heart rate and its variability are modeled by a Kalman filter. In the second approach, the signal is divided into windows according to the beats. Stacking the windows constructs a tensor that is then decomposed. In a third approach, the signal is not directly modeled, but it is considered as a Gaussian process characterized by its second order statistics. In all the different proposed methods, unlike previous studies, mECG and fECG(s) are explicitly modeled. The performances of the proposed methods, which utilize a minimal number of electrodes, are assessed on synthetic data and actual recordings including twin fetal cardiac signals.

The aim of this master thesis is to create a 3D electroanatomical model of a heart atria, which would be able to perform atrial fibrillation. To control the model, the differential equations of the FitzHugh-Nagumo model were chosen. These equations describe the change of voltage on the cell membrane. The equations have established parameters. The modification of them leads to changes in the behavior of the model. The simulations were performed in the COMSOL Multiphysics environment. In the first step, the simulations were performed on 2D models. Simulations of healthy heart, atrial flutter and atrial fibrillation were created. The acquired knowledge served as a basis for the creation of a 3D model on which atrial fibrillation was simulated on the basis of ectopic activity and reentry mechanism. Convincing results were obtained in accordance with the used literature. The advantages of computational modeling are its availability, zero ethical burden and the ability to simulate even rarer arrhythmias. The disadvantage of the procedure is the need to compromise between accuracy and computational complexity of simulations.