Pasinaudojant Henkelio matricomis tiriamas elektrokardiogramos ir jos parametrų kompleksiškumas. Po to, elektrokardiogramos fragmentai aprašomi eksponenčių baigtine sume. Taip pat pasiūlytas algoritmas, kaip pasinaudojant koreliacija dvylika standartinių derivacijų pakeisti trimis laisvai pasirenkamomis. / The method how to reinstate standard ECG lead by means of correlation and by three freely chosen ECG leads is suggested in this work. Next method is to evaluate complexity, to analyze, how many components are needed to record ECG and ECG parameters. Also we try to describe ECG fragment using exponential sum.

Background: Atrial fibrillation (AF) is the most common arrhythmia in the adult population, affecting about 5% of the population over 65 years. Occurrence of AF is an independent risk factor for stroke, and together with other cardiovascular risk factors (CHADS2/CHA2DS2- VASc), the stroke risk increases. Since AF is often paroxysmal and asymptomatic (silent) it may remain undiagnosed for a long time and many AF patients are not discovered before suffering a stroke. Aims: To estimate the prevalence of previously undiagnosed AF in an out-of-hospital population with CHADS2 ≥1, in patients with an enlarged left atrium (LA) and of total AF prevalence in sleep apnea (SA) patients, conditions that have been associated with AF. To compare the efficacy of short intermittent ECG with continuous 24h Holter ECG in detecting arrhythmias. Methods: Patients without known AF recorded 10−30 second handheld ECG (Zenicor-EKG®) registrations during 14−28 days at home, both regular, asymptomatic registrations twice daily and when having cardiac symptoms. Recordings were transmitted through the in-built SIM card to an internet-based database. Patients with palpitations or dizziness/presyncope referred for 24h Holter ECG were asked to additionally record 30-second handheld ECG registrations during 28 days at home. Results: In the out-of-hospital population with increased stroke risk, previously unknown AF was diagnosed in 3.8% of 928 patients. Comparing AF detection in patients with an enlarged LA versus normal LA showed that eleven of 299 patients had AF. Five of these had an enlarged LA (volume/BSA). No statistical difference in AF prevalence was found between patients with enlarged and normal LA, 3.3% and 3.2% respectively, (p = 0.974). AF occurred in 7.6% of 170 patients with sleep apnea, in 15% of patients with sleep apnea ≥60 years, and in 35% of patients with central sleep apnea. AF prevalence was also associated with severity of sleep apnea, male gender and diabetes. Comparing the efficacy of arrhythmia detection in 95 patients with palpitations or dizziness/presyncope with continuous 24h Holter and short intermittent ECG, 24h Holter found AF in two and AV-block II in one patient, resulting in 3.2% relevant arrhythmias detected. Short intermittent ECG diagnosed nine patients with AF, three with PSVT and one with AV-block II, in total 13.7% relevant arrhythmias. (p = 0.0094). Conclusions: Screening in the out-of-hospital patient population (mean age 69.8 years) yielded almost 4% AF, making it seem worthwhile to screen older patients with increased stroke risk for AF with this method. Screening patients with LA enlargement (mean age 73.1 years) did not result in higher detection rates compared with the general out-of-hospital population. AF occurred in 7.6% of patients with sleep apnea, (mean age 57.6 years) and was associated with severity of sleep apnea, presence of central sleep apnea, male gender, age ≥60 years, and diabetes. Short intermittent ECG is more effective in detecting relevant arrhythmias than 24h Holter ECG in patients with palpitations or dizziness/presyncope.

Κατά τη διάρκεια των δύο τελευταίων δεκαετιών, στο χώρο της τεχνολογίας έχουν αναπτυχθεί δίαφορα ενσωματωμένα συστήματα λήψης σημάτων φυσιολογίας, ικανά να καταγράφουν σύνθετα σήματα για πάνω απο 48 ώρες. Η εξέλιξη αυτή βοήθησε ιδιαίτερα τον τομέα της βιοϊατρικής. Τέτοια ενσωματωμένα συστήματα χρησιμοποιούνται στις μελέτες ηλεκτροκαρδιογραφίας (ECG ή EKG) για τον εντοπισμό σποραδικών αρρυθμιών ή ανωμαλιών στη καρδιακή λειτουργία.Σήμερα τα καρδιακά σήματα καταγράφονται σε κάρτες μνήμης και μπορούν εύκολα να μεταφερθούν για ανάλυση και επεξεργασία. Η εξέλιξη της τεχνολογίας επιφέρει συνεχως αλλαγές και βελτιώσεις στις συσκευές καταγραφής ΗΚΓ, περιορίζοντας συνεχώς το μέγεθός τους και την κατανάλωσή τους σε ενέργεια. Στην εργασία αυτή θα παρουσιαστούν ενσωματωμένα συστήματα καταγραφής, αποθήκευσης και επεξεργασίας ηλεκτροκαρδιογραφικών σημάτων.Η εργασία αυτή χωρίζεται ουσιαστικά σε πέντε κομμάτια. Το πρώτο τμήμα ασχολείται με τη φυσιολογία της καρδιάς, με τη δομή ενός ηλεκτροκαρδιογράφου και τους τρόπους με τους οποίους μπορούμε να το λάβουμε από τα διάφορα σημεία του ανθρώπινου σώματος.Το επόμενο τμήμα αφορά τη χρήση και τις δυνατότητες των ενσωματωμένων συστημάτων και μικροελεγκτών δίνοντας μεγαλύτερη έμφαση στην παρουσίαση του μικροελεγκτή ADUC7026 και των περιφερειακών του. Επιπλέον συνοψίζονται κάποιες βασικές λειτουργίες προγραμματισμού και δυνατότητες που παρουσιάζει ο ADUC7026 της Analog Devices και παρουσιάζονται κάποιες βασικές εφαρμογές του.Το τρίτο τμήμα επικεντρώνεται στην ανάλυση κάποιων τεχνικών κατασκευής ψηφιακών συσκευών παρακολούθησης καρδιακού παλμού με τη χρήση πυκνωτικών ηλεκτροδίων. Η ανάλυση περιλαμβάνει, τα υλικά από τα οποία αποτελούνται, τα χαρακτηριστικά τους, την αποδοτικότητά τους στην αντιμετώπιση του θορύβου και μια γενικότερη αξιολόγησή τους.Το τέταρτο τμήμα ασχολείται με μια πιο προηγμένη τεχνική καταγραφής σήματος που πραγματοποιείται ασύρματα. Αναλύεται τόσο ο τρόπος κατασκεής ασύρματων συσκευών μέτρησης ΗΚΓ όσο και ο τρόπος χρήσης τους. Στη συνέχεια αυτού του κεφαλαίο δίνεται βάση στην ανάλυση του μικροελεγκτή MSP430FG439 της Olimex και στη χρήση του στη μέτρηση ΗΚΓ.Στο τελευταίο τμήμα δίνεται ο κώδικας προγραμματισμού του μικροελεγκτή MSP430 για την καταγραφή ηλεκτροκαρδιογραφήματος και μία σχετική επεξήγηση της λειτουργίας του. / During the last two decades there have been developed embedded systems, for the receive of physiology signals, that are able to record composite signals for more than 48 hours. This evolution plays a very important role in the field of biomedics. These embedded systems are used at research on electrocardiography (ECG) for the locating of sporadic cardiac arrhythmias, or abnormal heart function.Nowadays, cardiac signals are recorded on memory cards and can easily be transferred for analysis and processing. The technological evolution brings a lot of changes and improvements on the recording devices of ECG, reducing their size and the power they consume. At this thesis, embedded systems for recording, saving and processing ECG signals are presented. The thesis is divided into five sections. The first part deals with the physiology of the heart, the structure of the electrocardiograph and how we can receive it from different parts of the human body. The next section covers the use and potential of embedded systems and microcontrollers emphasizing on presentation of the microcontroller ADUC7026 and its peripherals. In addition, some basic programming functions are summarized and three basic applications of ADUC7026 of Analog Devices are presented. The third section focuses on analyzing methods of constructing digital devices for heartbeat monitoring with the use of capacitive electrodes. Constructive materials, features, efficiency in dealing with noise and a more general evaluation, are included in the analysis.The fourth section refers to a more advanced method of recording signals that has wireless function. The method of constructing wireless ECG recording devices and their usage are also analyzed here. In this section, microcontroller MSP430FG439 of Olimex is presented and there is a description about its use on ECG measurements.At the last section there is the programming code of MSP430 for ECG recording and a brief explanation of its function and purpose.

Les maladies cardiovasculaires sont l'une des principales causes de mortalité chez l'homme. Une façon de diagnostiquer des maladies cardiaques et des anomalies est le traitement de signaux cardiaques tels que le ECG. Dans beaucoup de ces traitements, des caractéristiques inter-battements et intra-battements de signaux ECG doivent être extraites. Ces caractéristiques comprennent les points de repère des ondes de l’ECG (leur début, leur fin et leur point de pic), les intervalles significatifs et les segments qui peuvent être définis pour le signal ECG. L'extraction des points de référence de l'ECG consiste à identifier l'emplacement du pic, de début et de la fin de l'onde P, du complexe QRS et de l'onde T. Ces points véhiculent des informations cliniquement utiles, mais la segmentation precise de chaque battement de l'ECG est une tâche difficile, même pour les cardiologues expérimentés.Dans cette thèse, nous utilisons un cadre bayésien basé sur le modèle dynamique d'ECG proposé par McSharry. Depuis ce modèle s'appuyant sur la morphologie des ECG, il peut être utile pour la segmentation et l'analyse d'intervalles d'ECG. Afin de tenir compte de la séquentialité des ondes P, QRS et T, nous utiliserons également l'approche de Markov et des modèles de Markov cachés (MMC). En bref dans cette thèse, nous utilisons un modèle dynamique (filtre de Kalman), un modèle séquentiel (MMC) et leur combinaison (commutation de filtres de Kalman (SKF)). Nous proposons trois méthodes à base de filtres de Kalman, une méthode basée sur les MMC et un procédé à base de SKF. Nous utilisons les méthodes proposées pour l'extraction de points de référence et l'analyse d'intervalles des ECG. Le méthodes basées sur le filtrage de Kalman sont également utilisés pour le débruitage d'ECG, la détection de l'alternation de l'onde T, et la détection du pic R de l'ECG du foetus.Pour évaluer les performances des méthodes proposées pour l'extraction des points de référence de l'ECG, nous utilisons la base de données "Physionet QT", et une base de données "Swine" qui comprennent ECG annotations de signaux par les médecins. Pour le débruitage d'ECG, nous utilisons les bases de données "MIT-BIH Normal Sinus Rhythm", "MIT-BIH Arrhythmia" et "MIT-BIH noise stress test". La base de données "TWA Challenge 2008 database" est utilisée pour la détection de l'alternation de l'onde T. Enfin, la base de données "Physionet Computing in Cardiology Challenge 2013 database" est utilisée pour la détection du pic R de l'ECG du feotus. Pour l'extraction de points de reference, la performance des méthodes proposées sont évaluées en termes de moyenne, écart-type et l'erreur quadratique moyenne (EQM). Nous calculons aussi la sensibilité des méthodes. Pour le débruitage d'ECG, nous comparons les méthodes en terme d'amélioration du rapport signal à bruit. / Cardiovascular diseases are one of the major causes of mortality in humans. One way to diagnose heart diseases and abnormalities is processing of cardiac signals such as ECG. In many of these processes, inter-beat and intra-beat features of ECG signal must be extracted. These features include peak, onset and offset of ECG waves, meaningful intervals and segments that can be defined for ECG signal. ECG fiducial point (FP) extraction refers to identifying the location of the peak as well as the onset and offset of the P-wave, QRS complex and T-wave which convey clinically useful information. However, the precise segmentation of each ECG beat is a difficult task, even for experienced cardiologists.In this thesis, we use a Bayesian framework based on the McSharry ECG dynamical model for ECG FP extraction. Since this framework is based on the morphology of ECG waves, it can be useful for ECG segmentation and interval analysis. In order to consider the time sequential property of ECG signal, we also use the Markovian approach and hidden Markov models (HMM). In brief in this thesis, we use dynamic model (Kalman filter), sequential model (HMM) and their combination (switching Kalman filter (SKF)). We propose three Kalman-based methods, an HMM-based method and a SKF-based method. We use the proposed methods for ECG FP extraction and ECG interval analysis. Kalman-based methods are also used for ECG denoising, T-wave alternans (TWA) detection and fetal ECG R-peak detection.To evaluate the performance of proposed methods for ECG FP extraction, we use the "Physionet QT database", and a "Swine ECG database" that include ECG signal annotations by physicians. For ECG denoising, we use the "MIT-BIH Normal Sinus Rhythm", "MIT-BIH Arrhythmia" and "MIT-BIH noise stress test" databases. "TWA Challenge 2008 database" is used for TWA detection and finally, "Physionet Computing in Cardiology Challenge 2013 database" is used for R-peak detection of fetal ECG. In ECG FP extraction, the performance of the proposed methods are evaluated in terms of mean, standard deviation and root mean square of error. We also calculate the Sensitivity for methods. For ECG denoising, we compare methods in their obtained SNR improvement.

A interpretação dos gráficos gerados em exames com eletrocardiogramas (ECG) requer profissionais da área da saúde treinados para identificar as oscilações elétricas que resultam da atividade do coração. Ainda assim, pequenas alterações podem não ser percebidas, ou desprezadas, eliminando chances potenciais de detecção de patologias em estágios iniciais. A grande maioria dos procedimentos automatizados para a análise de ECGs é baseada em técnicas de filtragem digitais e estatísticas, nas quais geralmente se verifica a desvantagem não apenas do custo computacional, como também a perda da qualidade do sinal e o consequente comprometimento das informações extraídas. O presente trabalho lança mão de filtros com premissas geométricas que preservam essas informações e ainda contribuem para a redução no número de pontos redundantes contidos em um ECG. Também propõe a criação de uma identidade cardíaca capaz de traduzir o padrão morfológico único e característico de cada paciente. Foram analisados ECGs de 52 indivíduos saudáveis, e a redução de pontos alcançada foi de mais de 95%. Por fim, o desenvolvimento de uma ferramenta gráfica apresentou uma nova abordagem que viabiliza tanto uma análise personalizada do ECG, como também um acompanhamento da condição cardíaca ao longo da vida. / An interpretation of the graphs generated on electrocardiograms exams (ECG) requires trained healthcare professionals to identify the electrical oscillations that result from heart activity. Even so, small changes can not be perceived, and clinical changes may be neglected, eliminating potential chances of detection of pathologies still in early stages. The large majority of automated procedures for analysis of ECGs are based on digital and statistical filtering techniques, in which it usually occurs beyond computational cost, loss of signal quality and the resulting compromise of extracted information. The present work makes use of filters with geometric premises that preserve this information and also contribute to the reduction in the number of redundant points contained in an ECG. It also proposes the creation of a cardiac identity capable of translating the unique and characteristic morphological pattern of each patient. ECGs were analyzed from 52 healthy individuals, and the reduction of points achieved was greater than 95%. Finally, the development of a graphical tool presented a new approach that enables both a personalized ECG analysis and a monitoring of the cardiac condition throughout life.

Cardiovascular disease is a leading cause of death in developed countries, and places a huge demand on healthcare services and economies across the globe. In this thesis computational models of the rabbit and mouse whole heart were developed and used to investigate a variety of phenomena related to cardiac electrophysiology. In part I, a heterogeneous family of single cell models was developed for the rabbit ventricles. The models were incorporated into a 3D anatomical reconstruction, and subsequently used to study the relationship between ventricular heterogeneity and the electrocardiographic T-wave. It was found that, in order of significance, apico-basal, inter-ventricular and transmural heterogeneity had a lead-dependent effect on the T-wave of the 12-lead electrocardiogram. Subsequently, a detailed model of the rabbit whole heart was developed using image data from X-ray computed tomography, from which detailed anatomical structures were segmented and myocardial architecture determined. The developed 3D whole heart model exhibited physiological fibre structure and experimentally justified patterns of activation. In part II, a mathematical model of the mouse atrioventricular node was developed. The model was validated by its ability to show physiological pacemaking and response to ion channel blocking. The model was subsequently adapted to consider the heterogeneous nature of the atrioventricular node, and incorporated into a 2D simplistic tissue model of the whole heart. The developed model exhibited physiological atrioventricular conduction, and provided insights into the nature of dual-pathway electrophysiology and the role of the funny current. Finally, an optimisation study was carried out for contrast enhancement of X-ray computed tomography, specifically for imaging the mouse heart, the results of which may be used to facilitate future high-throughput imaging of cardiac tissue.

A interpretação dos gráficos gerados em exames com eletrocardiogramas (ECG) requer profissionais da área da saúde treinados para identificar as oscilações elétricas que resultam da atividade do coração. Ainda assim, pequenas alterações podem não ser percebidas, ou desprezadas, eliminando chances potenciais de detecção de patologias em estágios iniciais. A grande maioria dos procedimentos automatizados para a análise de ECGs é baseada em técnicas de filtragem digitais e estatísticas, nas quais geralmente se verifica a desvantagem não apenas do custo computacional, como também a perda da qualidade do sinal e o consequente comprometimento das informações extraídas. O presente trabalho lança mão de filtros com premissas geométricas que preservam essas informações e ainda contribuem para a redução no número de pontos redundantes contidos em um ECG. Também propõe a criação de uma identidade cardíaca capaz de traduzir o padrão morfológico único e característico de cada paciente. Foram analisados ECGs de 52 indivíduos saudáveis, e a redução de pontos alcançada foi de mais de 95%. Por fim, o desenvolvimento de uma ferramenta gráfica apresentou uma nova abordagem que viabiliza tanto uma análise personalizada do ECG, como também um acompanhamento da condição cardíaca ao longo da vida. / An interpretation of the graphs generated on electrocardiograms exams (ECG) requires trained healthcare professionals to identify the electrical oscillations that result from heart activity. Even so, small changes can not be perceived, and clinical changes may be neglected, eliminating potential chances of detection of pathologies still in early stages. The large majority of automated procedures for analysis of ECGs are based on digital and statistical filtering techniques, in which it usually occurs beyond computational cost, loss of signal quality and the resulting compromise of extracted information. The present work makes use of filters with geometric premises that preserve this information and also contribute to the reduction in the number of redundant points contained in an ECG. It also proposes the creation of a cardiac identity capable of translating the unique and characteristic morphological pattern of each patient. ECGs were analyzed from 52 healthy individuals, and the reduction of points achieved was greater than 95%. Finally, the development of a graphical tool presented a new approach that enables both a personalized ECG analysis and a monitoring of the cardiac condition throughout life.

Diabetes mellitus (DM) is not just a simple metabolic disorder, however, it is considered to be a cardiovascular disease of a metabolic origin. This is apparent especially when speaking about type 2 diabetes (DM II). Patients with DM have a high occurrence of vegetative nervous system (VNS) disorders that manifest themselves as an increased activity of the sympathetic nervous system that correlates with peripheral autonomic neuropathy and is considered to be the major pathophysiological mechanism for the development of DM II. The objective of our study was to determine whether a comprehensive spa treatment (ST) may affect the level of the sympathetic tone of patients suffering from DM II. As an indicator of the sympathetic tone, selected electrocardiographic parameters derived from the HRV, microvolt T-wave alternans, and microvolt R-wave alternans were evaluated. The electrophysiological examination of patients was performed before and after a three-week spa treatment using the KARDiVAR system. The method is used to examine the current state of the autonomic nervous system and carry out an analysis of risk factors and adaptive capabilities of the organism. The results showed favorable changes in DM II patients after the ST, primarily in terms of reduced sympathetic adrenal system activity,...

A fibrilação atrial (FA) é um dos tipos mais freqüentes de arritmia cardíaca e é caracterizada principalmente pela aleatoriedade na ocorrência dos batimentos do coração. Sob este aspecto, a fibrilação atrial pode ser considerada um processo estocástico e por isso tem sido freqüentemente modelada através de cadeias de Markov. Seguindo trabalhos anteriores sobre este tópico, este trabalho modela seqüências temporais de batimentos cardíacos como um processo markoviano de três estados para detecção automática de FA. O modelo foi treinado e desenvolvido através dos sinais da base de dados MIT-BIH. Outro método mais consolidado na detecção de FA, denominado \"Razão RR\", também foi implementado, com o objetivo de comparar os resultados do Modelo Markoviano. A avaliação de desempenho para ambos os métodos implementados fo i realizada medindo-se a sensibilidade (Se) e o valor preditivo positivo (+P) para a detecção de FA. Estes dois métodos - Modelos Markovianos e \"Razão RR\" - tiveram seus coeficientes e limiares otimizados com o objetivo de maximizar, ao mesmo tempo, os valores de Se e +P. Após a otimização, ambos os métodos foram testados com uma nova base de dados, independente da base de dados de desenvolvimento. Os resultados obtidos com a base de dados de teste foram Se=84,940% e +P=81,579%, consolidando os Modelos Markoviano s para detecção de batimentos aleatórios. / Atrial fibrillation (AF) is one of the most common cardiac arrhythmia and it is mainly characterized by the presence of random RR intervals. In this way, atrial fibrillation has been studied as a stochastic process and it has been often modeled through Markov chains. Following previous studies on this subject, this work models time sequences of heartbeats as a three states Markov process for AF automatic detection. The model was trained and developed using signals from MIT-BIH database. Another consolidated method for AF detection, called \"RR Ratios\", was also applied to compare Markov Model\'s results. The performance evaluation of both methods was measured through sensitivity (Se) and positive predictive (+P) for AF detection. These two methods - Markov Model and \"RR Ratio\" - had their coefficients and thresholds optimized in order to maximize the values of Se and +P at the same time. After optimization, both methods were tested with another database, independent of development database. The obtained results were Se = 84,940% and +P = 81,579%, consolidating Markov Models for detecting random heartbeats.

Master of Science / Department of Electrical and Computer Engineering / Steven Warren / A reference design for a wearable, wireless biomedical sensor set has been a long-term need for researchers at Kansas State University, driven by the idea that a basic set of sensor components could address the demands of multiple types of human and animal health monitoring scenarios if these components offered even basic reconfigurability. Such a reference design would also be a starting point to assess sensor performance and signal quality in the context of various biomedical research applications. This thesis describes the development of a set of wireless health monitoring sensors that can be used collectively as a data acquisition platform to provide biomedical research data and to serve as a baseline reference design for new sensor and system development. The host computer, an Intel Edison unit, offers plug-and-play usability and supports both Wi-Fi and Bluetooth wireless connectivity. The reference sensor set that accompanies the Intel Edison single-board computer includes an electrocardiograph, a pulse oximeter, and an accelerometer/gyrometer. All sensors are based on the same physical footprint and connector placement so that the sensors can be stacked to create a collection with a minimal volume and footprint. The latest hardware version is 3.1. Version 1.0 supported only a pulse oximeter, whereas version 2.0 included an electrocardiograph, pulse oximeter, and respiration belt. In version 3.0, the respiration belt was removed, and accelerometers and gyroscopes were added to the sensor set. Version 3.1 is a refined version of the latter design, where known hardware bugs were remedied. Future work includes the development of new sensors and casing designs that can hold these sensor stacks.