Background: ST-elevation acute myocardial infarction (STEMI) represents one of the leading causes of death. The time of STEMI onset has a circadian rhythm with a peak during diurnal hours, and the occurrence of STEMI follows a seasonal pattern with a salient peak of cases in the winter months and a marked reduction of cases in the summer months. Scholars investigated the reason behind the winter peak, suggesting that environmental and climatic factors concur in STEMI pathogenesis, but no studies have investigated whether the circadian rhythm is modified with the seasonal pattern, in particular during the summer reduction in STEMI occurrence. Methods and Results: Here, we provide a multiethnic and multination epidemiological study (from both hemispheres at different latitudes, n=2270 cases) that investigates whether the circadian variation of STEMI onset is altered in the summer season. The main finding is that the difference between numbers of diurnal (6:00 to 18:00) and nocturnal (18:00 to 6:00) STEMI is markedly decreased in the summer season, and this is a prodrome of a complex mechanism according to which the circadian rhythm of STEMI time onset seems season dependent. Conclusions: The “summer shift” of STEMI to the nocturnal interval is consistent across different populations, and the sunshine duration (a measure related to cloudiness and solar irradiance) underpins this season-dependent circadian perturbation. Vitamin D, which in our results seems correlated with this summer shift, is also primarily regulated by the sunshine duration, and future studies should investigate their joint role in the mechanisms of STEMI etiogenesis.

Work is aimed at the time-frequency decomposition of a signal application for monitoring the EKG trend progression. Goal is to create algorithm which would watch changes in the ST segment in EKG recording and its realization in the Matlab program. Analyzed is substance of the origin of EKG and its measuring. For trend calculations after reading the signal is necessary to preprocess the signal, it consists of filtration and detection of necessary points of EKG signal. For taking apart, also filtration and measuring the signal is used wavelet transformation. Source of the data is biomedicine database Physionet. As an outcome of the algorithm are drawn ST segment trends for three recordings from three different patients and its comparison with reference method of ST qualification. For qualification of the heart stability, as a system, where designed methods watching differences in position of the maximal value in two-zone spectrum and the Poincare mapping method. Realized method is attached to this thesis.

Les récentes avancées dans le domaine de la miniaturisation des capteurs biomédicaux à ultra-faible consommation énergétique, permettent aujourd’hui la conception de systèmes de télésurveillance médicale, à la fois plus intelligents et moins invasifs. Ces capteurs sont capables de collecter des signaux vitaux tels que le rythme cardiaq ue, la température, la saturation en oxygène, la pression artérielle, l'ECG, l'EMG, etc., et de les transmettre sans fil à un smartphone ou un autre dispositif distant. Ces avancées sus-citées ont conduit une large communauté scientifique à s'intéresser à la conception de nouveaux systèmes d'analyse de données biomédicales, en particulier de l’électrocardiogramme (ECG). S’inscrivant dans cette thématique de recherche, la présente thèse s’intéresse principalement à l’analyse et à la détection automatique des maladies cardiaques coronariennes, en particulier l’ischémie myocardique et l’infarctus du myocarde (IDM). A cette fin, et compte tenu de la nature non stationnaire et fortement bruitée du signal ECG, le premier défi a été d'extraire les paramètres pertinents de l’ECG, sans altérer leurs caractéristiques essentielles. Cette problématique a déjà fait l’objet de plusieurs travaux et ne représente pas l’objectif principal de cette thèse. Néanmoins, étant un prérequis incontournable, elle a nécessité une étude et une compréhension de l'état de l'art afin de sélectionner la méthode la plus appropriée. En s'appuyant sur les paramètres ECG extraits, en particulier les paramètres relatifs au segment ST et à l'onde T, nous avons contribué dans cette thèse par deux approches d'analyse ECG : (1) Une première analyse réalisée au niveau de la série temporelle des paramètres ECG, son objectif est de détecter les élévations anormales du segment ST et de l'onde T, connues pour être un signe précoce d'une ischémie myocardique ou d’un IDM. (2) Une deuxième analyse réalisée au niveau des battements de l’ECG, dont l’objectif est la classification des anomalies du segment ST et de l’onde T en différentes catégories. Cette dernière approche est la plus utilisée dans la littérature, cependant, il est difficile d’interpréter les résultats des travaux existants en raison de l'absence d’une méthodologie standard de classification. Nous avons donc réalisé notre propre étude comparative des principales méthodes de classification utilisées dans la littérature, en prenant en compte diverses classes d'anomalies ST et T, plusieurs paramètres d'évaluation des performances ainsi que plusieurs dérivations du signal ECG. Afin d'aboutir à des résultats plus significatifs, nous avons également réalisé la même étude en prenant en compte la présence d'autres anomalies cardiaques fréquentes dans l’ECG (arythmies). Enfin, en nous basant sur les résultats de cette étude comparative, nous avons proposé une nouvelle approche de classification des anomalies ST-T en utilisant une combinaison de la technique du Boosting et du sous-échantillonnage aléatoire, notre objectif étant de trouver le meilleur compromis entre vrais-positifs et faux-positifs. / Recent advances in sensing and miniaturization of ultra-low power devices allow for more intelligent and wearable health monitoring sensor-based systems. The sensors are capable of collecting vital signs, such as heart rate, temperature, oxygen saturation, blood pressure, ECG, EMG, etc., and communicate wirelessly the collected data to a remote device and/or smartphone. Nowadays, these aforementioned advances have led a large research community to have interest in the design and development of new biomedical data analysis systems, particularly electrocardiogram (ECG) analysis systems. Aimed at contributing to this broad research area, we have mainly focused in this thesis on the automatic analysis and detection of coronary heart diseases, such as Ischemia and Myocardial Infarction (MI), that are well known to be the leading death causes worldwide. Toward this end, and because the ECG signals are deemed to be very noisy and not stationary, our challenge was first to extract the relevant parameters without losing their main features. This particular issue has been widely addressed in the literature and does not represent the main purpose of this thesis. However, as it is a prerequisite, it required us to understand the state of the art proposed methods and select the most suitable one for our work. Based on the ECG parameters extracted, particularly the ST segment and the T wave parameters, we have contributed with two different approaches to analyze the ECG records: (1) the first analysis is performed in the time series level, in order to detect abnormal elevations of the ST segment and the T wave, known to be an accurate predictor of ischemia or MI; (2) the second analysis is performed at the ECG beat level to automatically classify the ST segment and T wave anomalies within different categories. This latter approach is the most commonly used in the literature. However, lacking a performance comparison standard in the state of the art existing works, we have carried out our own comparison of the actual classification methods by taking into account diverse ST and T anomaly classes, several performance evaluation parameters, as well as several ECG signal leads. To obtain more realistic performances, we have also performed the same study in the presence of other frequent cardiac anomalies, such as arrhythmia. Based on this substantial comparative study, we have proposed a new classification approach of seven ST-T anomaly classes, by using a hybrid of the boosting and the random under sampling methods, our goal was ultimately to reach the best tradeoff between true-positives and false-positives.

Elektrokardiografi är en vanligt förekommande undersökning inom hälso- och sjukvården då undersökningen är icke-invasiv och ger en bra överblick över hjärtats elektrofysiologiska status. Ett vanligt fel vid EKG är elektrodplacering i andra respektive tredje intercostala utrymmet istället för i fjärde intercostala utrymmet (IC4), vilket bland annat kan medföra reducering av R-vågs amplituden samt påverka datortolkningen. Syftet med arbetet var att se om avvikande EKG-kurvor uppstår vid omplacering av elektroderna V1 och V2 i andra och tredje intercostala utrymmet vid jämförelse med fjärde intercostala utrymmet på friska vuxna. I studien ingår 50 deltagare i åldern 18-48. Den statistiska analysen utfördes med hjälp av parvis T-test samt Fisher exact test. Jämförelsen mellan de olika placeringarna resulterade i en signifikant minskning av R-vågsamplituden (p <0,001) för samtliga kombinationer. En signifikant minskning visades i R-vågsduration i jämförelsen Intercostalrum 2 (IC2) versus (vs) IC4 i V2. För ST-sträckan visade båda avledningarna för jämförelsen IC2 vs IC4 en signifikant skillnad (p<0,001). Datortolkningen visade en signifikant skillnad för IC2 vs IC4 (p0,006) samt IC3 vs IC4 (p<0,001).  Omplacering av elektroder medför förändrad datortolkning när det vid en standardplacering visar ett normalt EKG, vilket kan ge en inverkan på patientens fortsatta handläggning och eventuella diagnos. / Electrocardiography is commonly used in healthcare as the examination is non-invasive and provides a good overview of the heart's electrophysiological status. A common error in ECG positioning is placement in the second or third intercostal space, which among other things can lead to a reduction in R wave amplitude and affect the computer interpretation. The aim of the study is to see if deviant ECG curves occur when repositioning the electrodes V1 and V2 in the second and third intercostal space when compared to the fourth intercostal space. The study includes 50 healthy adults aged 18-48. The statistical analysis was performed using paired t tests and Fisher exact test. The comparison resulted in a significant reduction in R wave amplitude (p <0.001) for all combinations. A significant decrease was shown in R wave duration in the comparison of IC2 vs IC4 in V2. For the ST segment, both leads for the comparison IC4 vs IC2 a significant difference was presented (p <0.001). For the computer interpretation, a significant difference was shown for IC2 vs IC4 (p0.006) and IC3 vs IC4 (p<0.001). Repositioning of electrodes leads to a different computer interpretation when in standard positioning shows a normal ECG, which may lead to misdiagnosis.

Background: ST-elevation acute myocardial infarction (STEMI) represents one of the leading causes of death. The time of STEMI onset has a circadian rhythm with a peak during diurnal hours, and the occurrence of STEMI follows a seasonal pattern with a salient peak of cases in the winter months and a marked reduction of cases in the summer months. Scholars investigated the reason behind the winter peak, suggesting that environmental and climatic factors concur in STEMI pathogenesis, but no studies have investigated whether the circadian rhythm is modified with the seasonal pattern, in particular during the summer reduction in STEMI occurrence. Methods and Results: Here, we provide a multiethnic and multination epidemiological study (from both hemispheres at different latitudes, n=2270 cases) that investigates whether the circadian variation of STEMI onset is altered in the summer season. The main finding is that the difference between numbers of diurnal (6:00 to 18:00) and nocturnal (18:00 to 6:00) STEMI is markedly decreased in the summer season, and this is a prodrome of a complex mechanism according to which the circadian rhythm of STEMI time onset seems season dependent. Conclusions: The “summer shift” of STEMI to the nocturnal interval is consistent across different populations, and the sunshine duration (a measure related to cloudiness and solar irradiance) underpins this season-dependent circadian perturbation. Vitamin D, which in our results seems correlated with this summer shift, is also primarily regulated by the sunshine duration, and future studies should investigate their joint role in the mechanisms of STEMI etiogenesis.