The work is devoted to solving the scientific and practical problem of automating the heart’s electrical axis calculation to improve 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” manufactured 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.

This work is devoted to solving the scientific and practical problem of morphological analysis of electrocardiograms based on an integral biomedical signal with locally concentrated features. In modern conditions of introduction of telemedicine in the health care system of Ukraine the creation of cardiological decision support systems based on automatic morphological analysis of electrocardiogram is of particular importance. The authors proposed a method for synthesizing an integral electrocardiogram in the frontal plane from all limb leads, taking into account the lead angle in the hexaxial reference system and the position of the heart’s electrical axis, since integral electrocardiological signals allow to obtain more accurate results compared to conventional electrocardiogram, because they take into account the individual characteristics of patients, a wide variety of electrocardiogram waveforms and complexes, which is associated not only with the presence of pathological processes in the myocardium, but also with the position of the electrical axis of the heart, in particular, the electrocardiogram will not register a low-amplitude P wave in the II department in the case of a horizontal electrical axis, but it will be clearly visible on the integral signal. To implement the method proposed in the article, a program was written in the MATLAB language, , the high speed of computation and good optimization of which allow to obtain results much faster and more accurate than using traditional approaches, and using the MATLAB Runtime library, which does not require licensing and is distributed free of charge, it was possible to provide more economical development, as well as to implement interaction with popular operating systems, which makes it more accessible and versatile. 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”. The paper shows that the proposed method for the synthesis of an integral signal with locally concentrated features will improve the quality of morphological analysis of electrocardiograms in cardiological decision support systems.

This 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.

Сучасна медицина характеризується різким зростанням кількості інформації, що переробляється при вирішенні традиційних лікарських завдань: від реєстрації біомедичної інформації до постановки діагнозу, визначення прогнозу, вибору та корекції тактики лікування за результатами діагнозу. Принциповою перевагою аналізу біомедичних даних за допомогою медичних інформаційних систем є можливість одномоментної оцінки багатьох параметрів з обробкою великих обсягів інформації, що не під силу ні людині, ні автоматичним аналізаторам, орієнтованим лише на обрані методи аналізу. Для підвищення ефективності електрокадріологічного дослідження було виконано системний аналіз процесу вироблення діагностичних рішень з метою виділення критичних елементів кардіологічної системи підтримки прийняття рішень, які можуть призвести до вироблення некоректних рішень або відмови від прийняття рішення. Метою дослідження є розробка функціональної моделі електрокадріологічного дослідження з використанням методології функціонального моделювання IDEF0. Результати. Запропановано функціональну модель електрокадріологічного дослідження у вигляді контекстної діаграми, її декомпозиції та декомпозиції робіт «Виконати реєстрацію та аналіз елктрпокардіограми» й «Виконати діагностики». Розроблена функціональна модель електрокадріологічного дослідження показала, що найвідповідальніші роботи виконуються особою, яка приймає рішення, за допомогою кардіологічної системи підтримки прийняття рішень. Крім того запропонована функціональна модель електрокадріологічного дослідження дозволила виділити різні режими роботи кардіологічної системи підтримки прийняття рішень (автоматичний, напівавтоматичний та ручний). Запропонована функціональна модель електрокадріологічного дослідження є основою розробки структури кардіологічної системи підтримки прийняття рішень.