Automatic detection of P, QRS and T patterns in 12 leads ECG signal based on CWT

International audienceIn this paper, a new method based on the continuous wavelet transform is described in order to detect the QRS, P and T waves. QRS, P and T waves may be distinguished from noise, baseline drift or irregular heartbeats. The algorithm, described in this paper, has been evaluated using the Computers in Cardiology (CinC) Challenge 2011 database and also applied on the MIT-BIH Arrhythmia database (MITDB). The data from the CinC Challenge 2011 are standard 12 ECG leads recordings with full diagnostic bandwidth compared to the MITDB which only includes two leads for each ECG signal. Firstly, our algorithm is validated using fifty 12 leads ECG samples from the CinC collection. The samples have been chosen in the "acceptable records" list given by Physionet. The detection and the duration delineation of the QRS, P and T waves given by our method are compared to expert physician results. The algorithm shows a sensitivity equal to 0.9987 for the QRS complex, 0.9917 for the T wave and 0.9906 for the P wave. The accuracy and the Youden index values show that the method is reliable for the QRS, T and P waves detection and delineation. Secondly, our algorithm is applied to the MITDB in order to compare the detection of QRS wave to results of other some works in the literature

Classification of Cardiac Arrhythmia in vitro based on Multivariate Complexity Analysis

International audienceBackground: The animal models (in vitro or in vivo) provide an excel-lent tool to study heart diseases, among them the arrhythmia remains one of the most active research subjects. It can be induced or treated by drugs, electrical stimulation, hypothermia etc.Problems: However, the inducing or treating effects in cardiac culture often happened long after the initial applications or in some relatively short time windows. So, it is necessary to capture and classify rapidly the signal change. Human-assisted monitoring is time-consuming and less efficient. An automatic classification method for real-time use would be useful and necessary. Methods: Since electrocardiological signals are features by repetitive or similar patterns reflecting the intrinsic information about the pa-tient (or culture), analyzing these patterns could help not only to monitor the status's change but also to evaluate/explore the physiol-ogic control mechanisms. Methods based on complexity analysis are of considerable interest in this case. Aims: Compare different complexity analysis methods in order to find the most appropriate ones to discriminate the normal cardiac signals from arrhythmic ones acquired from a cardiac cell culture in vitro. The selected features are then used by a SVM classifier.Results: Among the six complexity analysis methods, Time Lagging (TLag) method allowed obtaining the best discrimination index (nor-mal vs. arrhythmic, p-value, 9e-23). The proposed Modified Hurst Exponent (HExM) showed better performance than original Hurst Exponent with well-improved p-value (from 0.019 to 2e-9). The Ap-proximate Entropy (ApEn), Sample Entropy (SampEn) and Detrended Fluctuation Analysis gave good discrimination ratio but with larger p-values (at order 10^{-3}). Combination of TLag, HExM and ApEn can provide a more robust classifier and allow monitoring and classifying in an automatic way the electrical activities' changes in the cardiac cultures

Analyse et détection des électrogrammes complexes fractionnés en vue de soigner la fibrillation auriculaire à l'aide de techniques d'ablation par radiofréquence

Ce manuscrit présente des travaux de recherche sur l analyse et la détection des Electrogrammes Auriculaires Complexes Fractionnés (EACF). Dans une première partie faisant suite à une présentation des mécanismes et des signaux bioélelectriques de la Fibrillation Auriculaire (FA), les outils les plus couramment utilisés pour l analyse des signaux EACF sont présentés. Des outils linéaires sont dans un premier temps appliqués aux signaux intracardiaques issus des procédures d ablation de la FA par radiofréquence puis des outilsnon linéaires sont présentés et intégrés à un algorithme de détection des EACF. Ce dernier s appuie sur la quantification des propriétés de récurrence des électrogrammes. Dans la seconde partie, la cellule et le tissu musculaire cardiaque sont détaillés puis simulés à l aide de plusieurs modèles mathématiques. Ceux de FitzHugh Nagumo, Aliev Panfilov et Courtemanche Ramirez Nattel sont mis en oeuvre afin de reproduire les mécanismes de la FA évoqués dans la présentation de cette pathologie. L acquisition des champs de potentiels est également reproduite à l aide d un modèle numérique de cathéter tel que celui utilisé lors des procédures. Les signaux temporels ainsi générés permettent de lier les activations spatiotemporelles au niveau du substrat aux motifs observables dans les EACF. Un modèle expérimental vient compléter la partie modélisation. Les cultures de cellules de rats nouveaux nés sur puces MEA (Micro Electrode Array) permettent de recréer des conditions de fibrillation et d acquérir des potentiels extracellulaires. Là encore, les électrogrammes sont comparés aux signaux issus des simulations numériques ainsi qu aux signaux cliniques. L analyse des séquences de motifs via les trois types de modèles utilisés permet de rattacher les motifs observés dans les électrogrammes aux mécanismes se produisant au niveau du tissu cardiaque lors de la FA. Une analyse en temps réel permettrait de fournir au praticien des informations déterminantes lors de l ablation concernant la nature et la localisation des sources d arythmieThis manuscript presents research on the analysis and the detection of Complex Fractionated Atrial Electrograms (CFAE). In the first part, following a presentation over Atrial Fibrillation (AF) mechanisms and bioelectrical signals, the most commonly used tools for analyzing CFAE are presented. Linear tools are initially applied to signals from AF ablation procedures, then nonlinear tools are shown and integrated intoa CFAE detection algorithm. This one is based on the quantification of electrogram recurrence properties. In the second part, the cell and cardiac muscle tissue are described and simulated using mathematical models. Models such as FitzHugh Nagumo, Aliev Panfilov and Courtemanche Ramirez Nattel are implemented to reproduce the mechanisms of AF mentioned in the presentation of this disease. The acquisition of fields of potential is also reproduced using a numerical model of catheter as the one used during ablation process. Time signals thus generated are used to match the spatiotemporal activations at the substrate level with the patterns to be observed in CFAE. An experimental model completes the analysis. Cell cultures of newborn rats on MEA (Micro ElectrodeArray) can recreate fibrillation conditions and acquire extracellular potentials. Again, electrogramsare compared with signals from computer simulations and the clinical database signals. The analysisof pattern sequence via the three types of models can attach the observed patterns in electrograms with the mechanisms occurring at the cardiac tissue level during AF. Real-time analysis would allow the practitioner to receive critical information during ablation about the nature and the location of arrhythmia sourcesDIJON-BU Doc.électronique (212319901) / SudocSudocFranceF

In Vitro Arrhythmia Generation by Mild Hypothermia - a Pitchfork Bifurcation Type Process

International audienceThe neurological damage after cardiac arrest (CA) constitutes a big challenge of hospital discharge. The therapeutic hypothermia (34°C-32°C) has shown its benefit to reduce cerebral oxygen demand and improve neurological outcomes after the cardiac arrest. However, it can have many adverse effects, among them the cardiac arrhythmia generation represents an important part (up to 34%, according different clinical studies). Monolayer cardiac culture is prepared with cardiomyocytes from new-born rat directly on the multi-electrodes array, which allows acquiring the extracellular potential of the culture. The temperature range is 37°C - 30°C - 37°C, representing the cooling and rewarming process in the therapeutic hypothermia. Both experiments showed that at 35°C, the acquired signals are characterized by period-doubling phenomenon, compared to signals at any other temperatures. Spiral waves, commonly considered as a sign of cardiac arrhythmia, are observed in the reconstructed activation map. With an approach from nonlinear dynamics, phase space reconstruction, it is shown that at 35°C, the trajectories of these signals formed a bifurcation, even trifurcation. Another transit point is found between 30°C - 33°C, which agreed with other clinical studies that induced hypothermia after cardiac arrest should not be below 32°C. The therapeutic hypothermia after cardiac arrest can be represented by a Pitchfork bifurcation, which could explain the different ratio of arrhythmia among the adverse effects after this therapy. This nonlinear dynamics suggests that a variable speed of cooling / rewarming, especially when passing 35°C, would help to decrease the ratio of post-hypothermia arrhythmia and then improve the hospital output

Complexity analysis of experimental cardiac arrhythmia

International audienceTo study the cardiac arrhythmia, an in vitro experimental model and Multielectrodes Array (MEA) are used. This platform serves as an intermediary of the electrical activities of cardiac cells and the signal processing / dynamics analysis. Through it the extracellular potential of cardiac cells is acquired, allowing a real-time monitoring / analyzing. Since MEA has 60 electrodes / channels dispatched in a rectangular region, it allows real-time monitoring and signal acquisition on multiple sites. The in vitro experimental model (cardiomyocytes cultures from new-born rats' heart) is directly prepared on the MEA. This carefully prepared culture has similar parameters as cell of human's heart. In order to discriminate the cardiac arrhythmia, complexity analysis methods (Approximate Entropy, ApEn and Sample Entropy, SampEn) are used especially taking into account noise. The results showed that, in case of arrhythmia, the ApEn and SampEn are reduced to about 50\% of the original entropies. Both parameters could be used as factors to discriminate arrhythmia. Moreover, from a point of view of biophysics this decrease 50\% of Entropy coincides with the bifurcation (periods, attractors etc.) in case of arrhythmia which have been reported previously. It supports once more the hypothesis that in case of cardiac arrhythmia, the heart entered into chaos which helps to better understand the mechanism of atrial fibrillation

Modélisation, Analyse et Traitement de l'Information

Mes activités de recherche s’articulent, d’une part, autour de l’instrumentation et du génie biomédical,et, d’autre part, autour du traitement et de la transmission non linéaire de l’information. Elles sebasent sur la modélisation des signaux à partir de modèles non linéaires (principalement modèles deréaction-diffusion. . . ) continus (EDP) et discrets (numériques). Dans cette partie, d’un point de vuefondamental, des phénomènes dynamiques complexes ou chaotiques sont caractérisés à travers l’analyse,la classification, la reconnaissance des motifs dans des signaux physiologiques ou issus des circuitsélectroniques. Un autre axe sur lequel je travaille concerne l’analyse et le traitement des données issuesde plusieurs modalités physiques utilisées dans le domaine de l’expertise des composants électroniques àforte intégration. L’amélioration du rapport signal sur bruit des données acquises, la reconnaissance, ladétection et la localisation des défauts à partir de ces données constituent les problématiques abordées.Ce mémoire d’HDR est organisé comme suit : Dans le premier chapitre, un CV très détaillé permet de faire un bilan de mes activités derecherche (notamment les publications, les projets et les encadrements de jeunes chercheurs),d’enseignement et d’administration. A la fin de ce chapitre, j’introduit le contexte général de mesactivités de recherche. Ensuite, dans les chapitres 2, 3 et 4, mes activités de recherche sont décrites à travers les thèses quej’ai co-encadrées. Quelques unes de mes publications sont jointes pour illustrer mes contributionsà l’état de l’art. Enfin, je clos ce manuscrit avec mes perspectives sur la partie recherche

New Approach of Controlling Cardiac Alternans

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Improvement of the Detection of the QRS Complex, T and P Waves in an Electrocardiogram Signal using 12 Leads versus 2 Leads

International audienceThe electrical field potential of the heart recorded from the thoracic part of the human body is depicted by the electrocardiogram signal. This last one is complex and depends on many factors: Position of heart, thickness of the body skin, surface electrode conductivity, acquisition noise and many others. In clinical use, the ECG signal is analysed using twelve leads but in many works in the literature, the analysis methods of the ECG is based on two leads. We present a new method to delineate QRS complexes and T and P waves from electrocardiogram signal. It is based on the continuous wavelet transform. The method is applied on several leads, recorded simultaneously, to improve the localization of the detection. Indeed, if a delineation method is applied on only one lead with some disturbances in it, the result of the delineation could be affected. As the method proposed here merges the result of several leads, the delineation is less affected by disturbances on few leads. The results from this method and from a doctor in medicine are compared. That shows the good ability to separate waves and the enhancement of delineation accuracy when several leads are used