This thesis deals with acquisition and wireless transmission of EKG from isolated heart. Basic of heart anatomy and physiology are discussed in thesis. Practical part of thesis covers the idea of ECG acqusition system design and development. Arduino platform is used for implementation of proposed device. Evaluation of ECG is performed in Matlab workspace.

SUDEP bezeichnet den plötzlichen und unerwarteten Epilepsietod ohne offensichtliche kausale Todesursache. Junge Patienten, die an der schweren infantilen enzephalo-pathischen Epilepsieform des Dravet-Syndroms (SMEI) leiden, tragen besonderes Risiko an SUDEP zu versterben. Die pathophysiologische Ursache für das Dravet-Syndrom liegt in einem Defekt des brain-type Natriumkanals Nav1.1. Neuere Studien zeigen, dass der ursprünglich als hirnspezifisch geltende Kanal nicht explizit in neuronalem Gewebe, sondern auch im Herzen exprimiert wird. Ziel dieser Arbeit war es daher, die Auswirkungen des Nav1.1-Defektes auf kardialer Ebene zu evaluieren, um eine mögliche Beteiligung von Herzrhythmusstörungen an der Ätiologie des SUDEP aufzudecken. Dazu wurde ein Knockout-Mausmodell hinsichtlich seines kardialen Phänotyps charakterisiert. Mit Hilfe elektrokardiographischer Untersuchungen (EKG) konnte eine gesteigerte Herzfrequenz unter Stressbedingungen festgestellt werden. Die Frequenz lag sowohl bei den Versuchen unter pharmakologischem Stress mittels Isoproterenol als auch unter induziertem Stress mittels Hyperthermie bei den Dravet-Syndrom-Mäusen höher als in dem wildtypischen Kontrollkollektiv. Elektrophysiologische Untersuchungen (EPU) zeigten neben einem erhöhten Schweregrad der induzierbaren Arrhythmien, gemessen anhand eines Arrhythmie-Scores, auch eine erhöhte Quantität ausgelöster Herzrhythmusstörungen. Sowohl unter Ruhebedingungen als auch nach Induktion von Hyperthermie überwogen die aufgezeichneten Arrhythmien bei Dravet-Syndrom-Mäusen. Die Erkenntnisse dieser Studie helfen die Rolle des Nav1.1-Defektes an einer kardialen Beteiligung im Rahmen von SUDEP bei Dravet-Patienten zu beschreiben. Sie zeigen ver-schiedene kardiale Auswirkungen bei Knockout des primär neuronalen Natrium¬kanalgens SCN1A. Weitere Einsichten in diesen Bereich werden angemessene Risikostratifizierung für Epilepsie-Patienten hinsichtlich Ihres SUDEP-Risikos ermöglichen und moderne The-rapieansätze anregen. / Voltage-gated sodium channels (Nav) are responsible for the initiation of action potentials in excitable cells. In this context distinct isoforms of the Nav sodium channel family seem to be important for both neuronal and cardiac excitation. It is known that mutation or knock out of the so called brain type sodium channel Nav1.1-isoform causes a spectrum of epilepsies including severe myoclonic epilepsy of infancy (SMEI) or Dravet Syndrome which is associated with a high risk of sudden unexpected death in epilepsy (SUDEP). Previously it was demonstrated that the brain type sodium channel isoform Nav1.1 is not exclusively expressed in the nervous system but also functionally present in cardiac tissue. Therefore, we hypothesize that patients suffering from neurologic Nav1.1-deseases carry an increased cardiac arrhythmia burden that may be responsible for SUDEP. We characterize the cardiac pathophysiology in an established mouse model of Dravet Syndrome. We used classical surface electrocardiogram recordings (ECG) and invasive programmed stimulation (EPU). This was done under stressing conditions by pharmacological adrenergic application (Isoproterenol) and hyperthermia (39°C). We found that heart rate under stressing conditions was elevated by knock out of Nav1.1 gene. Also arrhythmia inducibility was elevated which was seen in quality and quantity as well. This study helps to describe the role of defect Nav1.1 sodium channel in elevated SUDEP risk of Dravet Syndrome by possible cardiac genesis. Further studies will probably lead to stratify the SUDEP risk in order to find new therapies like implantable cardiac devices.

This project deals with anatomy and electrophysiology of heart. It describes the structure of cardiac muscle, mechanism of myocard's contraction, heart work, the origin and registration of electric signals of heart – electrocardiogram (ECG) and vectorcardiogram (VCG). Part of the work is design and creation of a software application for calculation and graphical presentation of vectorcardograms, useful for experimental data available on ÚBMI VUT in Brno.

This work deals with delineation of ECG signals. First we will become familiar with ECG and commonly used processing methods. Various transformation methods of ECG leads. Further we will describe methods of delineation ECG signals. Second part is dedicated to metod used in this work for delineation of ECG signals from CSE database. Particulary method using Dyadic Wavelet Transform. Work include, description of used program and results. Third part is dedicated to methods of ECG leads transformations and cluster analysis. In conclusion we will evaluate the results.

Heart arrhythmias are a very common heart disease whose incidence is rising. This thesis is focused on the detection of premature ventricular contractions from 12-lead ECG records by means of deep learning. The location of these arrhythmias (key instances) in the record was found using a technique based on Multiple-Instance Learning. In the theoretical part of the thesis, basic electrophysiology of the heart and deep learning with a focus on the convolutional neural networks are described. Afterward, a program was created using the Python programming language, which contains a model based on the InceptionTime architecture, using which classification of the signals into the selected classes was performed. Grad-CAM was implemented to find locations of the key instances in the ECGs. The evaluation of the arrhythmia detection quality was done using the F1 score and the results were discussed at the end of the thesis.

This seminar work deals with the topic of evaluating the quality of ECG signals. The introductory chapters explain the basic characteristics of ECG signals - measurement, the form of the measured signal, methods of analysis. The cardiac physiology and pathology is presented. The most common types of noise that occur in ECG signals are also mentioned. Further, the reader is acquainted with the importance of the issue of evaluating the quality of ECG signals. In the practical part of the work, two own methods for ECG quality evaluation are presented. First, a brief theoretical introduction to the techniques used in the creation of methoda is given, followed by a description of the principle of algorithms. In order to compare the functionality of the proposed methods, three more methods from other authors are presented. Their principle is briefly described. In the final chapter, all methods are subjected to functionality testing. The results are examined and all methods are compared with each other.

This master's thesis deals with an analysis of principles of ECG signals detection and delineation. The theoretical part describes heart electrophysiology and electrocardiography basics. Next, the most important QRS detection and ECG delineation algorithms are introduced. Especially the wavelet transform methods are described. In the practical part proper delineation algoriythm was realized. It was tested on the standard CSE database, then it was modified on data of isolated rabbit heartsand the results are published in the conclusion.

This master's thesis describes basics principles of QRS complex detection. It is focused on QRS detection using zero crossing counts method. There are described princips and program realization of this method. The other part is focused on genetic optimalization algorithm. There are presented obtained optimalization results on standard CSE and MIT-BIH database. The quality of the detector is compared with other authors. The optimalized QRS detector achieves comparable results with other authors. The part of the thesis is graphical user interface which supply view on modified ECG signal and detection results.

The master thesis deals with the issue of gaining the respiratory rate from ECG and PPG signals, which are not only in clinical practice widely used measurable signals. The theoretical part of the work outlines the issue of obtaining a breath curve from these signals. The practical part of the work is focused on the implementation of five selected methods and their final evaluation and comparison.

This work deals with ECG signal measuring and methods of its processing. It compares some of the QRS detection methods and describes some of the testing databases. In this work a detector of QRS complex is realized, it is based on the approach of zero crossings. Next section makes combination of results from separate leads to one, which improves efficiency of detection. One section of this work deals with design and realization delination of ECG signal. In the last part outputs of this delineation are compared with the results of the other authors.