Afin d’apporter les soins adéquats aux victimes d'arrêt cardiaque extrahospitalier, l'évaluation de leur état hémodynamique est primordiale. La prise de pouls manuelle ne permet pas une identification fiable de l'arrêt cardiaque par les profanes ou une discrimination des rythmes organisés par les premiers intervenants. Dans ce contexte, l'entreprise Schiller Médical a cherché à intégrer dans sa gamme de défibrillateurs un module de détection de l'hémodynamique systémique par analyse de l'électrocardiogramme et des variations d'impédance transthoracique recueillis via les électrodes de défibrillation. Ce travail de recherche mené en partenariat entre l'entreprise Schiller Médical et l'Institut Pluridisciplinaire Hubert Curien de l’Université de Strasbourg a consisté dans un premier temps a recherché, lors d'arrêt cardiaque induit électriquement chez l'homme, des descripteurs des variations d'impédance transthoracique marqueurs de l’hémodynamique systémique. L’identification des descripteurs les plus pertinents a par la suite permis de construire des modèles prédictifs des défaillances circulatoires. Nous avons mis en lumière des limites à l’utilisation des variations d’impédance transthoracique. Elles sont prises en considération pour la documentation des interventions extrahospitalières destinée à l’apprentissage des algorithmes de classification des rythmes perfusants et rythmes sans pouls. / Providing suitable emergency care during out of hospital cardiac arrest requires the diagnostic of the circulatory status. Manual pulse check does not provide a reliable way for laypersons to identify cardiac arrest or for first responders to discriminate organized rhythms. Thus, Schiller Medical sought to embed an hemodynamic sensor in its external defibrillators by analyzing the electrocardiogram and transthoracic impedance recorded via the defibrillation pads. This thesis work stemmed from a partnership between Schiller Medical and the Institut Pluridisciplinaire Hubert Curien of the Université de Strasbourg. We first identified transthoracic impedance featureslinked with the circulatory status by studying clinically induced cardiac arrest. The most relevant features were later selected to form predictive models of hemodynamic collapse. We uncovered restrictions to the use of transthoracic impedance. We took them into account for the annotation of out of hospital cardiac arrests aimed at training algorithms for the classification of pulseless electrical activity and pulsatile rhythms.

Introdução: O miocárdio não compactado (MNC) é uma cardiomiopatia rara, cujas principais manifestações clínicas são insuficiência cardíaca, embolias e arritmias. A evolução desses pacientes é pouco conhecida. Dessa forma, o objetivo desse estudo é analisar o seguimento tardio de pacientes com MNC isolado ou associado a outras doenças, adultos e crianças com a doença, e de seus familiares, que foram acompanhados em hospital universitário de cardiologia, bem como avaliar os desfechos clínicos e de exames de imagem em cardiologia nesses pacientes. Métodos: Pacientes com diagnóstico de MNC confirmado por critérios ecocardiográficos e/ou ressonância magnética cardíaca (RMC) foram selecionados. Durante seu acompanhamento, foram convocados familiares de primeiro, segundo e terceiro graus para rastreamento da doença. Foram avaliados os seguintes desfechos: óbito, transplante cardíaco, eventos embólicos como acidente vascular cerebral (AVC) isquêmico, tromboembolismo pulmonar, embolia arterial periférica, internações hospitalares por insuficiência cardíaca (IC), ocorrência arritmias ventriculares complexas, e índices de exame de imagem como eletrocardiograma, Holter 24 horas, ecocardiograma transtorácico e RMC, que poderiam apresentar valor prognóstico nesses pacientes. Crianças (idade inferior a 12 anos) foram analisadas separadamente. Resultados: Foram acompanhados 215 pacientes com MNC, idade de 36,96 + 17,6 anos, 108 (50,2%) homens, que foram seguidos por 5,9 + 4,47 anos. Os pacientes foram divididos em 2 grupos: 193 com MNC isolado (Grupo 1) e 22 com MNC misto (associado a doenças genéticas, congênitas, doença de Chagas, coronariopatia, cardiomiopatia hipertrófica e miocardite de células gigantes; Grupo 2). A palpitação foi o sintoma clínico mais frequente, estando presente em 42,8% deles. A sobrevida foi menor nos pacientes do Grupo 2, nos que apresentaram FE do ventrículo esquerdo (VE) menor que 50% (p= 0,004), naqueles com aumento dos diâmetro e volume diastólicos finais do VE (p=0,018 e 0,017, respectivamente), com aumento do diâmetro do átrio esquerdo (p < 0,001), com disfunção diastólica do VE (p= 0,049), com disfunção sistólica do ventrículo direito (p= 0,003), nos que apresentaram internações hospitalares (p < 0,001), nos com eventos embólicos (p= 0,022), com arritmias ventriculares complexas (p= 0,010), com hipertensão arterial pulmonar pelo ecocardiograma (p < 0,001) . A ocorrência de FA foi estatisticamente significativa entre os pacientes com disfunção sistólica do VE (p= 0,0485) e todos os que apresentaram FA, tinham FEVE inferior a 40% (p= 0,048). Vinte e três pacientes eram crianças, seguidos por 4,41 ± 4,91 anos, idade média de 5,52 ± 3,62 anos, 12 (52,2%) do sexo masculino. A proporção de óbitos ou transplante cardíaco foi 3 vezes maior do que na população adulta (34,8%) e a IC foi o resultado mais comum. As arritmias cardíacas foram raras e os eventos embólicos não foram encontrados neste grupo. O rastreio familiar diagnosticou MNC em 36,7% dos pacientes. Na análise multivariada, a precocidade dos sintomas e a ocorrência de acidente vascular cerebral ou acidente isquêmico transitório foram os fatores mais importantes no prognóstico dos pacientes e capazes de predizer sobrevida (p < 0,001 e p= 0,008, respectivamente). Conclusão: O seguimento clínico e por métodos de imagens cardíacas por longo período de pacientes com MNC permite traçar um perfil dessa população e estimar o risco de complicações, reforçando a necessidade de diagnóstico e tratamento precoces. Em crianças, o MNC geralmente evolui de forma mais agressiva, com maior morbi-mortalidade. O rastreamento familiar consiste em uma ferramenta muito importante nesse contexto, permitindo a identificação de pacientes na fase subclínica da doença / Background: Non-compaction cardiomyopathy (NCC) is a rare disease, which main clinical manifestations are heart failure, arrhythmias and embolic events. The evolution of these patients is poorly known. Thus, the aims of this study was to analyze the late follow-up of patients with isolated NCC or associated with other diseases, adult and children with the disease and their relatives, which were followed at a university cardiology hospital, and to evaluate the clinical and the cardiology imaging outcomes in these patients. Methods: Patients with NCC confirmed by echocardiographic (echo) and / or cardiac magnetic resonance imaging (CMRI) criteria were selected. During their follow-up, their first, second and third degree relatives were recruited to perform screening of the disease using echo. The following variables were included: death, cardiac transplantation, embolic events such as stroke, pulmonary embolism, peripheral arterial embolism, hospital admissions for heart failure, complex ventricular arrhythmias, and imaging indexes of imaging exams such as electrocardiogram, Holter 24 hours, echocardiogram and CMRI, which could have prognostic value in these patients. Children (under 12 years old) were analyzed separately. Results: Two hundred and fifteen patients with NCC were followed for 5.9 ± 4.47 years, mean age of 36,96 ±17,6 years, 108 (50.2%) males. Patients were divided into 2 groups: 193 with isolated NCC (Group 1) and 22 with mixed NCC (associated with genetic and congenital diseases, Chagas disease, coronary disease, hypertrophic cardiomyopathy and giant cell myocarditis; Group 2). Palpitation was the most frequent clinical symptom, present in 42,8% of them. The survival rate was lower in Group 2 patients (p < 0.05), left ventricular (LV) ejection fraction (EF) less than 50% (p= 0.004), increased LV end-diastolic diameter and volume by echo (p= 0.018 and 0.017, respectively), with LV diastolic dysfunction (p= 0.049), with increased left atrium dimensions (p < 0,001), with right ventricular systolic dysfunction (p= 0.003), hospital admissions (p < 0.001), embolic events (p= 0.022), complex ventricular arrhythmias (p = 0.010) and pulmonary hypertension by echo (p < 0.001). All patients with isolated NCC and AF presented LVEF less than 0.40, and between patients without AF, only 41.7% presented LVEF less than 0.40 (p = 0.048). Twenty-three patients was children, followed for 4.41 ± 4.91 years, mean age of 5.52 ± 3.62 years, 12 (52.2%) males. The proportion of deaths or cardiac transplantation was 3 times higher than in the adult population (34,8%) and heart failure was the most common outcome. Cardiac arrhythmias were rare, and the embolic events were not found in this group. The familiar screening diagnosed NCC in 36.7% of the patients. In the multivariate analysis, the precocity of the symptoms and the occurrence of stroke or transient ischemic attack were the most important factors in the prognosis of this patients and it is able to predict survival (p < 0.001 and p= 0.008, respectively). Conclusion: The clinical and cardiac imaging methods allows us to draw a profile of this population and to estimate the risk of complications, emphasizing the need for early diagnosis and treatment. In children, NCC used to develop more severe disease. Family screening is a very important tool, allowing the identification of patients with subclinical stage of the disease

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.

Made available in DSpace on 2016-03-15T19:37:40Z (GMT). No. of bitstreams: 1 Luiz Carlos Ferreira Rodrigues.pdf: 3281430 bytes, checksum: ce62f748aa1e8330c7d6402e06d3d41f (MD5) Previous issue date: 2012-03-02 / The cardiopathies are currently, according the Ministério da Saúde, the second biggest cause of mortality among the Brazilians, behind only the brain vascular diseases. The motivation for the work here presented is the identification and classification of cardiopathies registered in Electrocardiogram exams, ECG, such as premature contractions, branches blocks, tachycardia and other rhythms disturbance. Due its easy application and low cost, the ECG is one of the resources more commonly used by researchers and health professionals in the assessment of cardiac conditions. The computational application developed in this study relies in the application of Wavelets Transforms for the digital signal processing of ECG, in extracting the morphologic characteristics, dynamics and spectral of the cycles of the signal and in the submission of these characteristics to two Support Vector Machines (SVM). The output of these two SVM's are combined as input to a Bayesian Network for the identification and classification of the cardiopathies. The characteristic of each cycle, morphologic and spectral, has it dimensionality reduced by Principal Component Analysis (PCA). The spectral characteristics are extracted by the extractions of the Wavelets Transforms coefficients of the signal, whilst the dynamics characteristics are defined by the interval between the global maxima of each cycle. For development, testings and validations of the application we utilize the MIT-BIH Arrhythmia database, made available by Massachusetts Institute of Technology (MIT). At the end of this work we demonstrate that the application is able to recognize and classify 8 types of heart beats in ECG records, with an medium accuracy above 95,0%. / As cardiopatias são atualmente, segundo o Ministério da Saúde, a segunda maior causa de mortalidade entre brasileiros, ficando atrás apenas das doenças cerebrovasculares. A motivação do trabalho aqui apresentado é a identificação e classificação de cardiopatias registradas em exames de Eletrocardiograma, o ECG, tais como contrações prematuras, bloqueio de ramos, taquicardias e outros distúrbios de ritmo. Devido a sua fácil aplicação e baixo custo, o ECG é um dos recursos mais largamente utilizados por pesquisadores e profissionais da saúde na avaliação da saúde do coração. A aplicação computacional desenvolvida neste estudo concentra-se no uso de Transformadas Wavelets para o processamento digital dos sinais de ECG, na extração das características morfológicas, dinâmicas e espectrais de ciclos do sinal e na submissão dessas características a duas Máquinas de Vetores de Suporte (SVM). Os resultados das SVM's são combinadas em uma Rede Bayesiana para a identificação e classificação das cardiopatias. As características morfológicas de cada ciclo do sinal são extraídas através de Análise de Componentes Principais (PCA), as características espectrais são extraídas através da decomposição do sinal em coeficientes de Transformadas Wavelets enquanto as características dinâmicas são definidas pelos intervalos entre o máximo global de cada ciclo. Para desenvolvimento, testes e validação da aplicação foi utilizado o Banco de Arritmias MIT-BIH, disponibilizado pelo Massachusetts Institute of Technology (MIT). Neste trabalho demonstramos que a aplicação desenvolvida é capaz de reconhecer e classificar 8 tipos de batimentos cardíacos em registros de ECG, com uma acurácia média total de classificação superior a 95,0%.

Introdução: O miocárdio não compactado (MNC) é uma cardiomiopatia rara, cujas principais manifestações clínicas são insuficiência cardíaca, embolias e arritmias. A evolução desses pacientes é pouco conhecida. Dessa forma, o objetivo desse estudo é analisar o seguimento tardio de pacientes com MNC isolado ou associado a outras doenças, adultos e crianças com a doença, e de seus familiares, que foram acompanhados em hospital universitário de cardiologia, bem como avaliar os desfechos clínicos e de exames de imagem em cardiologia nesses pacientes. Métodos: Pacientes com diagnóstico de MNC confirmado por critérios ecocardiográficos e/ou ressonância magnética cardíaca (RMC) foram selecionados. Durante seu acompanhamento, foram convocados familiares de primeiro, segundo e terceiro graus para rastreamento da doença. Foram avaliados os seguintes desfechos: óbito, transplante cardíaco, eventos embólicos como acidente vascular cerebral (AVC) isquêmico, tromboembolismo pulmonar, embolia arterial periférica, internações hospitalares por insuficiência cardíaca (IC), ocorrência arritmias ventriculares complexas, e índices de exame de imagem como eletrocardiograma, Holter 24 horas, ecocardiograma transtorácico e RMC, que poderiam apresentar valor prognóstico nesses pacientes. Crianças (idade inferior a 12 anos) foram analisadas separadamente. Resultados: Foram acompanhados 215 pacientes com MNC, idade de 36,96 + 17,6 anos, 108 (50,2%) homens, que foram seguidos por 5,9 + 4,47 anos. Os pacientes foram divididos em 2 grupos: 193 com MNC isolado (Grupo 1) e 22 com MNC misto (associado a doenças genéticas, congênitas, doença de Chagas, coronariopatia, cardiomiopatia hipertrófica e miocardite de células gigantes; Grupo 2). A palpitação foi o sintoma clínico mais frequente, estando presente em 42,8% deles. A sobrevida foi menor nos pacientes do Grupo 2, nos que apresentaram FE do ventrículo esquerdo (VE) menor que 50% (p= 0,004), naqueles com aumento dos diâmetro e volume diastólicos finais do VE (p=0,018 e 0,017, respectivamente), com aumento do diâmetro do átrio esquerdo (p < 0,001), com disfunção diastólica do VE (p= 0,049), com disfunção sistólica do ventrículo direito (p= 0,003), nos que apresentaram internações hospitalares (p < 0,001), nos com eventos embólicos (p= 0,022), com arritmias ventriculares complexas (p= 0,010), com hipertensão arterial pulmonar pelo ecocardiograma (p < 0,001) . A ocorrência de FA foi estatisticamente significativa entre os pacientes com disfunção sistólica do VE (p= 0,0485) e todos os que apresentaram FA, tinham FEVE inferior a 40% (p= 0,048). Vinte e três pacientes eram crianças, seguidos por 4,41 ± 4,91 anos, idade média de 5,52 ± 3,62 anos, 12 (52,2%) do sexo masculino. A proporção de óbitos ou transplante cardíaco foi 3 vezes maior do que na população adulta (34,8%) e a IC foi o resultado mais comum. As arritmias cardíacas foram raras e os eventos embólicos não foram encontrados neste grupo. O rastreio familiar diagnosticou MNC em 36,7% dos pacientes. Na análise multivariada, a precocidade dos sintomas e a ocorrência de acidente vascular cerebral ou acidente isquêmico transitório foram os fatores mais importantes no prognóstico dos pacientes e capazes de predizer sobrevida (p < 0,001 e p= 0,008, respectivamente). Conclusão: O seguimento clínico e por métodos de imagens cardíacas por longo período de pacientes com MNC permite traçar um perfil dessa população e estimar o risco de complicações, reforçando a necessidade de diagnóstico e tratamento precoces. Em crianças, o MNC geralmente evolui de forma mais agressiva, com maior morbi-mortalidade. O rastreamento familiar consiste em uma ferramenta muito importante nesse contexto, permitindo a identificação de pacientes na fase subclínica da doença / Background: Non-compaction cardiomyopathy (NCC) is a rare disease, which main clinical manifestations are heart failure, arrhythmias and embolic events. The evolution of these patients is poorly known. Thus, the aims of this study was to analyze the late follow-up of patients with isolated NCC or associated with other diseases, adult and children with the disease and their relatives, which were followed at a university cardiology hospital, and to evaluate the clinical and the cardiology imaging outcomes in these patients. Methods: Patients with NCC confirmed by echocardiographic (echo) and / or cardiac magnetic resonance imaging (CMRI) criteria were selected. During their follow-up, their first, second and third degree relatives were recruited to perform screening of the disease using echo. The following variables were included: death, cardiac transplantation, embolic events such as stroke, pulmonary embolism, peripheral arterial embolism, hospital admissions for heart failure, complex ventricular arrhythmias, and imaging indexes of imaging exams such as electrocardiogram, Holter 24 hours, echocardiogram and CMRI, which could have prognostic value in these patients. Children (under 12 years old) were analyzed separately. Results: Two hundred and fifteen patients with NCC were followed for 5.9 ± 4.47 years, mean age of 36,96 ±17,6 years, 108 (50.2%) males. Patients were divided into 2 groups: 193 with isolated NCC (Group 1) and 22 with mixed NCC (associated with genetic and congenital diseases, Chagas disease, coronary disease, hypertrophic cardiomyopathy and giant cell myocarditis; Group 2). Palpitation was the most frequent clinical symptom, present in 42,8% of them. The survival rate was lower in Group 2 patients (p < 0.05), left ventricular (LV) ejection fraction (EF) less than 50% (p= 0.004), increased LV end-diastolic diameter and volume by echo (p= 0.018 and 0.017, respectively), with LV diastolic dysfunction (p= 0.049), with increased left atrium dimensions (p < 0,001), with right ventricular systolic dysfunction (p= 0.003), hospital admissions (p < 0.001), embolic events (p= 0.022), complex ventricular arrhythmias (p = 0.010) and pulmonary hypertension by echo (p < 0.001). All patients with isolated NCC and AF presented LVEF less than 0.40, and between patients without AF, only 41.7% presented LVEF less than 0.40 (p = 0.048). Twenty-three patients was children, followed for 4.41 ± 4.91 years, mean age of 5.52 ± 3.62 years, 12 (52.2%) males. The proportion of deaths or cardiac transplantation was 3 times higher than in the adult population (34,8%) and heart failure was the most common outcome. Cardiac arrhythmias were rare, and the embolic events were not found in this group. The familiar screening diagnosed NCC in 36.7% of the patients. In the multivariate analysis, the precocity of the symptoms and the occurrence of stroke or transient ischemic attack were the most important factors in the prognosis of this patients and it is able to predict survival (p < 0.001 and p= 0.008, respectively). Conclusion: The clinical and cardiac imaging methods allows us to draw a profile of this population and to estimate the risk of complications, emphasizing the need for early diagnosis and treatment. In children, NCC used to develop more severe disease. Family screening is a very important tool, allowing the identification of patients with subclinical stage of the disease

Atrial fibrillation is diagnosed in 1-2% of the population, in next decades, it expects a significant increase in the number of patients with this arrhythmia in connection with the aging of the population and the higher incidence of some diseases that are considered as risk factors of atrial fibrillation. The aim of this work is to describe the problem of atrial fibrillation and the methods that allow its detection in the ECG record. In the first part of work there is a theory dealing with cardiac physiology and atrial fibrillation. There is also basic descreption of the detection of atrial fibrillation. In the practical part of work, there is described software for detection of atrial fibrillation, which is provided by BTL company. Furthermore, an atrial fibrillation detector is designed. Several parameters were selected to detect the variation of RR intervals. These are the parameters of the standard deviation, coefficient of skewness and kurtosis, coefficient of variation, root mean square of the successive differences, normalized absolute deviation, normalized absolute difference, median absolute deviation and entropy. Three different classification models were used: support vector machine (SVM), k-nearest neighbor (KNN) and discriminant analysis classification. The SVM classification model achieves the best results. Results of success indicators (sensitivity: 67.1%; specificity: 97.0%; F-measure: 66.8%; accuracy: 92.9%).

This thesis deals with classification of different types of time courses of ECG signals. Main objective was to recognize the normal cycles and several forms of arrhythmia and to classify the exact types of them. Classification has been done with usage of algorithms of Neural Networks in Matlab program, with its add-on (Neural Network Toolbox). The result of this thesis is application, which makes possible to load an ECG signal, pre-process it and classify its each cycle into five classes. Percentage results of this classification are in the conclusion of this thesis.

The goal of this thesis is to detect pacing pulses in ultra high-frequency ECG so as to remove these pacing pulses. It makes evaluation of higher frequency components of QRS complex possible. This evaluation is impossible while pacing pulses are present. Chosen issue is solved using heuristic algorithm. Algorithm uses spacing of signal by line in the area which is not influenced by pacing pulses. Subsequently this line is made longer and using differences between line and signal (or another rules) edges of pacing pulses are detected. The top of the stimulation tip is detected by thresholding envelope of original signal´s first difference. More algorithms are tested in this thesis. Several methods of removing pacing pulses are suggested in thesis. Envelopes of high-frequency components are created. Envelopes are analyzed subsequently and suggested methods of removing pacing pulses are compared on the basis of these analysis. Finally the detection efficiency is evaluated.

<p>Emerging technologies such as real-time travel information systems and automated vehicles (AVs) have profound impacts on driver decision-making behavior. While they generally have positive impacts by enabling drivers to make more informed decisions or by reducing their driving effort, there are several concerns related to inadequate consideration of cognitive and psychological aspects in their design. In this context, this dissertation analyzes different aspects of driver cognition and psychology that arise from drivers’ interactions with these technologies using physiological data collected in two sets of driving simulator experiments.</p> <p>This research analyzes the latent cognitive and psychological effects of real-time travel information using electroencephalogram (EEG) data measured in the first set of driving simulator experiments. Using insights from the previous analysis, a hybrid route choice modeling framework is proposed that incorporates the impacts of the latent information-induced cognitive and psychological effects along with other explanatory variables that can be measured directly (i.e., route characteristics, information characteristics, driver attributes, and situational factors) on drivers’ route choice decisions. EEG data is analyzed to extract two latent cognitive variables that capture the driver’s cognitive effort during and immediately after the information provision, and cognitive inattention before implementing the route choice decision. </p> <p>Several safety concerns emerge for the transition of control from the automated driving system to a human driver after the vehicle issues a takeover warning under conditional vehicle automation (SAE Level 3). In this context, this study investigates the impacts of driver’s pre-warning cognitive state on takeover performance (i.e., driving performance while resuming manual control) using EEG data measured in the second set of driving simulator experiments. However, there is no comprehensive metric available in the literature that could be used to benchmark the role of driver’s pre-warning cognitive state on takeover performance, as most existing studies ignore the interdependencies between the associated driving performance indicators by analyzing them independently. This study proposes a novel comprehensive takeover performance metric, Takeover Performance Index (TOPI), that combines multiple driving performance indicators representing different aspects of takeover performance. </p> <p>Acknowledging the practical limitations of EEG data to have real-world applications, this dissertation evaluates the driver’s situational awareness (SA) and mental stress using eye-tracking and heart rate measures, respectively, that can be obtained from in-vehicle driver monitoring systems in real-time. The differences in SA and mental stress over time, their correlations, and their impacts on the TOPI are analyzed to evaluate the efficacy of using eye-tracking and heart rate measures for estimating the overall takeover performance in conditionally AVs.</p> The study findings can assist information service providers and auto manufacturers to incorporate driver cognition and psychology in designing safer real-time information and their delivery systems. They can also aid traffic operators to incorporate cognitive aspects while devising strategies for designing and disseminating real-time travel information to influence drivers’ route choices. Further, the study findings provide valuable insights to design operating and licensing strategies, and regulations for conditionally automated vehicles. They can also assist auto manufacturers in designing integrated in-vehicle driver monitoring and warning systems that enhance road safety and user experience.

No description available.