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Документ Evaluating the Effectiveness of Electrocardiological Study Using Cardiological Decision Support Systems(2020) Filatova, A. E.; Skarga-Bandurova, Inna; Brezhniev, Eugene; Fahs, MohamadThis work is devoted to evaluating the effectiveness of the electrocardiological study process without using and using cardiological decision support systems. To assess the effectiveness, analytical expressions of the probabilistic-time characteristics of the developed structural model of the electrocardiological study process are used. An analysis of the time characteristics of the model is performed when different initial conditions are set for three different types of electrocardiological studies: the study is conducted for the first time, the study is repeated as a result of screening, the study is repeated after treatment. The work shows that the use of cardiological decision support systems based on the developed methods for analyzing biomedical signals with locally concentrated features reduced the average time required for the electrocardiological study of each of the considered types.Документ Method of automatic determination of the heart’s electrical axis in cardiological decision support systems(Одеський національний політехнічний університет, 2021) Filatova, A. E.; Fahs, MohamadThe work is devoted to solving the scientific and practical problem of automating the heart’s electrical axis calculation to im-prove the quality of morphological analysis of biomedical signals with locally concentrated features in cardiological decision support systems, which in turn reduces the likelihood of medical errors. The work shows that existing methods for in the determining the electrical axis of the heart require morphological analysis of an electrocardiogram. The method is based on determining the integral signal in the frontal plane from all limb leads, taking into account the lead angle in the hexaxial reference system. In graphic form in polar coordinates, the integral electrocardiological signal is a figure, predominantly elongated along the axis, the direction’n of which corresponds to the heart’s electrical axis. The position of the heart’s electrical axis is calculated as the angle between the axis of standard lead I and the vector, the end of which is at the center of mass of the locus of the points the farthest away from the reference point. Cluster analysis is used to find the most distant points from the reference point. The proposed method for of calculating the heart’s electrical axis makes it possible not to carry out a preliminary morphological analysis of an electrocardiogram. To implement the method proposed in the article, a program was written in the Matlab language, which is connected as a dynamic link library to the cardiological decision support system “TREDEX telephone” operating as part of the medical diagnostic complex “TREDEX” manu-factured by “Company TREDEX” LLC, Kharkiv. Verification of the results was carried out using a database of electrocardiograms, which were recorded using a transtelephone digital 12-channel electrocardiological complex “Telecard”, which is part of the medical diagnostic complex “TREDEX”, and deciphered by cardiologists of the communal non-profit enterprise of the Kharkiv Regional Council “Center for Emergency Medical aid and disaster medicine”. Comparison of the results of calculating the heart’s electrical axis according to electrocardiograms by a doctor and automatically using the proposed method showed that in the overwhelming majority of cases the decisions made coincide. At the same time, cardiologists make mistakes, and errors are made during automatic calculation using the proposed method. The paper explains the reasons for these errors.Документ Application of probabilistic-time graphs for evaluating the effectiveness of the electrocardiological study process(Одеський національний політехнічний університет, 2020) Filatova, A. E.; Povoroznyuk, A. I.; Fahs, MohamadThis work is devoted to the development of a structural model of the patient’s electrocardiological study process based on graph theory, probability theory and the method of generating functions. The developed structural model is presented in the form of a probabilistic-time graph, in which nine main states and an uncertainty state (a set of states that do not lead to the goal) are identified, as well as the probabilistic-time characteristics of the arcs of transitions from one graph state to another. The following are identified as the main states characterizing the process to complete an electrocardiological study: the beginning of the study; indications were defined; morphological analysis of biomedical signals with locally concentrated features was performed; pathological changes were identified; comparison with previous electrocardiological studies was performed; dynamics evaluation was completed; evaluation of treatment effectiveness was completed; diagnostic decision was made; recommendations were issued (the end of the electrocardiological study). For the proposed model of the electrocardiological study process by the Mason method, there are obtained analytical expressions for the generating functions of the entire graph, as well as the part of the graph that characterizes the successful completion of the electrocardiological study. Using the indicated generating functions, analytical expressions were obtained to calculate the average transit time of an electrocardiological study and the probability of successful completion of this process. To get all analytic expressions, a program was written in the Matlab language. The developed structural model of an electrocardiological study in the form of a probabilistic-time graph made it possible to identify the main states and determine the criteria for the effectiveness of the process in terms of average time and the probability of a successful study.Документ Оценка эффективности принятия решений в процессе электрокардиологического исследования(Екологія, 2020) Филатова, Анна Евгеньевна; Фахс, М.Данная работа посвящена оценке эффективности процесса электрокардиологического исследования без использования и с использованием кардиологических систем поддержки принятия решений. Для оценки эффективности используются полученные аналитические выражения вероятностно-временных характеристик разработанной структурной модели процесса электрокардиологического исследования. В работе показано, что использование кардиологических систем поддержки принятия решений, основанных на разработанных методах анализа биомедицинских сигналов с локально сосредоточенными признаками, сократило среднее время, необходимое для электрокардиологического исследования, и увеличило вероятность успешного завершения рассматриваемого процесса.Документ Development of alternative diagnostic feature system in the cardiology decision support systems(Технологический центр, 2016) Povoroznyuk, A. I.; Filatova, A. E.The trend towards an increase in the production of Ukrainian digital electrocardiographic telemetry systems such as transtelephonic digital 12-channel electrocardiograph complex "Telecard" identified the need to create intelligent automated cardiac decision support systems. The basis of these systems is the morphologic analysis of electrocardiograms, which represent biomedical signals with locally concentrated features. The system of alternative diagnostic features based on the method proposed by the authors of the morphological analysis of biomedical signals with locally concentrated features to provide additional graphical information in the diagnosis of one of the most common cardiac arrhythmias - ventricular arrhythmia is developed. Representation of the electrocardiogram in two-dimensional space of alternative features, as well as hodograph is proposed. Differences between the ECG-hodographs for normal ECG and ECG with different arrhythmias of right and left ventricles, as well as multifocal ventricular arrhythmia are analyzed. It was found that a graphical representation of an electrocardiogram in the alternative feature space allows the physician to visually perform the classification of different types of ventricular arrhythmia, which in combination with the classical analysis of ECG on the time axis increases the reliability of diagnostics.