Šiame darbe analizuotos įvairių laiko eilučių išlyginimo ir panašumo nustatymo metodų pritaikymo galimybės T bangų kaitos (TBK) analizėje, pagerinant Nearing ir Verrier pasiūlytą, modifikuoto slenkančio vidurkio metodą. Pasinaudojant TWA duomenų baze ir generuotais duomenimis surasti labiausiai TBK analizei tinkami išlyginimo ir panašumo vertinimo metodai. TBK, paskaičiuoto naudojant modifikuotą slenkančio vidurkio metodą papildytą TBK analizei tinkamiausiais laiko eilučių išlyginimo ir panašumo nustatymo metodais, tinkamumas širdies ligų diagnostikai patikrintas su duomenimis iš PTB duomenų bazės. Pasiremiant PTB duomenimis rastas galimas biomarkeris širdies ligų diagnostikoje, paskutinių dviejų TBK įverčių, gautų taikant MSVM su atviros pradžios ir pabaigos dinaminio laiko skalės kraipymo su asimetriniu judėjimo šablonu išlyginimą ir panašumą vertinant kaip absoliutinį skirtumą tarp maksimumo taškų, min-max kombinaciją. / T wave alternans (TWA) is a beat-to-beat change in the amplitude or shape of T wave. TWA is one of potential biomarkers for ventricular arrhythmias and can be a sign of serious heart disease. Because there is no gold standard in TWA measuring, modifications of existing methods and new solutions are possible. Modified moving average method, proposed by Nearing and Verrier, is one of mostly used in medical practise, but can give misleading results then T waves is not properly aligned or T wave length and morphology changes because of heart rate variability. It is known, that some ventricular arrhythmias can cause heart rate variability, so this type of error is unwanted, because online TWA measuring can become one of sudden ventricular arrhythmias predictors in the near future. In this work, variuos time series alignment and similarity detection techniques were used to improve TWA measuring and this measure capabilities in heart disease diagnostic were analized. TWA analysis with simulated and real data from ECG databases was performed and potentional biomarker was found by using biomarkers combining method, proposed by Liu, Liu and Halabi. 57.

Structural barriers can promote discordant action potential (AP) duration alternans, T wave alternans (TWA) and tachyarrhythmia in animal hearts and simulation studies. We hypothesized that heterogeneous scar (gray zone) and dense midwall scar (midwall core) would promote TWA in patients with cardiomyopathy by slowing conduction and uncoupling transmural APs, respectively. Scar core and gray zone were quantified in 40 cardiomyopathy patients using late gadolinium enhanced cardiac magnetic resonance imaging and related to the results of a clinically validated TWA test. The percentages of gray zone, epicardial core and midwall core were greater in the +TWA group, correlated with TWA magnitude and related to a lower heart rate onset for TWA. These specific scar patterns contribute to the genesis and severity of TWA in cardiomyopathy. Greater knowledge of the substrates that promote TWA in cardiomyopathy patients is valuable in determining those at risk of lethal ventricular arrhythmias.

Structural barriers can promote discordant action potential (AP) duration alternans, T wave alternans (TWA) and tachyarrhythmia in animal hearts and simulation studies. We hypothesized that heterogeneous scar (gray zone) and dense midwall scar (midwall core) would promote TWA in patients with cardiomyopathy by slowing conduction and uncoupling transmural APs, respectively. Scar core and gray zone were quantified in 40 cardiomyopathy patients using late gadolinium enhanced cardiac magnetic resonance imaging and related to the results of a clinically validated TWA test. The percentages of gray zone, epicardial core and midwall core were greater in the +TWA group, correlated with TWA magnitude and related to a lower heart rate onset for TWA. These specific scar patterns contribute to the genesis and severity of TWA in cardiomyopathy. Greater knowledge of the substrates that promote TWA in cardiomyopathy patients is valuable in determining those at risk of lethal ventricular arrhythmias.

Abstract There is a need to identify patients with an increased risk of dying after acute myocardial infarction (AMI), because sudden cardiac death (SCD) and potentially fatal ventricular tachyarrhythmias can be prevented by an implantable cardioverter-defibrillator, or in some cases, with aggressively optimized drug or revascularization therapy. The present study was designed to study the predictive power of non-invasive risk markers and all-cause, cardiac and arrhythmic mortality in 700 consecutive post-AMI patients discharged alive with optimal medication according to contemporary guidelines. Detrended fluctuation analysis of heart rate variability (HRV) predicted all-cause mortality beyond clinical variables as well as left ventricular function in post-AMI patients. The predictive power of the short-term scaling exponent α1 was higher than that of the traditional indexes of HRV (for α1 < 0.65, the risk ratio (RR) in multivariate analysis was 5.1, with 95% confidence intervals (CI) 2.9-8.9; p < 0.001). HRV results from a conventional 24-hour electrocardiographic (ECG) recording system differed significantly when compared to a system with a higher sampling frequency. The difference was generally more pronounced in post-AMI patients than in healthy subjects. The presence of sustained T-wave alternans during a predischarge exercise test after AMI was not a marker of mortality. However, the inability to perform an exercise test or to reach the heart rate of 105 beats/min predicted independently all-cause (RR 9.3, 95% CI 2.0-43.3, p < 0.01) and cardiac mortality (RR 11.1, 95% CI 2.4-50.8, p < 0.01). High levels of natriuretic peptides were associated with both sudden and non-sudden cardiac mortality. B-type natriuretic peptide provided more specific independent information on the risk for subsequent SCD (RR 3.9, 95% CI 1.2-12.3, p < 0.05) than non-SCD. SCDs occurred mainly more than 18 months after AMI, and the proportion of SCD was less than 40% of all cardiac deaths. Common arrhythmia markers such as the presence of ventricular premature beats or episodes of nonsustained ventricular tachycardia during ambulatory recordings, the time domain parameters of HRV, baroreflex sensitivity, QT dispersion and QRS complex duration provided only limited predictive power on the risk of SCD or arrhythmic events in patients with optimized beta-blocking therapy. Many risk variables previously considered to predict SCD were better predictors of non-SCD than SCD. Conclusions: 1. The epidemiological pattern of SCD was different from that reported previously. 2. Many arrhythmia risk markers provided only limited information on the risk of SCD. 3. Short-term fractal scaling exponent α1 provided potentially useful information on the risk for all-cause mortality, and BNP was useful in predicting the risk of SCD in a post-AMI population with optimized therapy.

No description available.

The thesis deals with possibilities of using wavelet transform in the field of surface electrocardiogram (ECG) signals denoising and ECG signals measuring. Several algorithms have been used to detect and estimate T-wave alternans (TWA), such as spectral method (SM), Poincaré Mapping (PM) or correlation method (CM). T-wave alternans, also called repolarization alternans, is a phenomenon appearing in the electrocardiogram as a consistent fluctuation in the repolarization morphology on every-other-beat basis. Electrical TWA has been recognized as a marker of electrical instability, and has been shown to be related with patients at increased risk for ventricular arrhytmias. Presence of TWA has been reported in a wide range of clinical and experimental situations including long QT syndrome, myocardial infarction, angina pectoris, acute ischemia, etc. Projected methods of detection TWA are realized in Matlab software, and they are experimentally verified on real ECG signals from the European ST-T Database.

No description available.

Cette thèse a pour objet l’étude de méthodes Bayésiennes pour l’analyse des ondes P et T des signaux ECG. Différents modèles statistiques et des méthodes Bayésiennes associées sont proposés afin de réaliser la détection des ondes P et T et leur caractérisation (détermination du sommet et des limites des ondes ainsi que l’estimation des formes d’onde). Ces modèles prennent en compte des lois a priori pour les paramètres inconnus (les positions des ondes, les amplitudes et les coefficients de ces formes d'onde) associés aux signaux ECG. Ces lois a priori sont ensuite combinées avec la vraisemblance des données observées pour fournir les lois a posteriori des paramètres inconnus. En raison de la complexité des lois a posteriori obtenues, des méthodes de Monte Carlo par Chaînes de Markov sont proposées pour générer des échantillons distribués asymptotiquement suivant les lois d’intérêt. Ces échantillons sont ensuite utilisés pour approcher les estimateurs Bayésiens classiques (MAP ou MMSE). D'autre part, pour profiter de la nature séquentielle du signal ECG, un modèle dynamique est proposé. Une méthode d'inférence Bayésienne similaire à celle développée précédemment et des méthodes de Monte Carlo séquentielles (SMC) sont ensuite étudiées pour ce modèle dynamique. Dans la dernière partie de ce travail, deux modèles Bayésiens introduits dans cette thèse sont adaptés pour répondre à un sujet de recherche clinique spécifique appelé détection de l'alternance des ondes T. Une des approches proposées a servi comme outil d'analyse dans un projet en collaboration avec St. Jude Medical, Inc et l'hôpital de Rangueil à Toulouse, qui vise à évaluer prospectivement la faisabilité de la détection des alternances des ondes T dans les signaux intracardiaques. / This thesis studies Bayesian estimation/detection algorithms for P and T wave analysis in ECG signals. In this work, different statistical models and associated Bayesian methods are proposed to solve simultaneously the P and T wave delineation task (determination of the positions of the peaks and boundaries of the individual waves) and the waveform-estimation problem. These models take into account appropriate prior distributions for the unknown parameters (wave locations and amplitudes, and waveform coefficients). These prior distributions are combined with the likelihood of the observed data to provide the posterior distribution of the unknown parameters. Due to the complexity of the resulting posterior distributions, Markov chain Monte Carlo algorithms are proposed for (sample-based) detection/estimation. On the other hand, to take full advantage of the sequential nature of the ECG, a dynamic model is proposed under a similar Bayesian framework. Sequential Monte Carlo methods (SMC) are also considered for delineation and waveform estimation. In the last part of the thesis, two Bayesian models introduced in this thesis are adapted to address a specific clinical research problem referred to as T wave alternans (TWA) detection. One of the proposed approaches has served as an efficient analysis tool in the Endocardial T wave Alternans Study (ETWAS) project in collaboration with St. Jude Medical, Inc and Toulouse Rangueil Hospital. This project was devoted to prospectively assess the feasibility of TWA detection in repolarisation on EGM stored in ICD memories.

No description available.

No description available.