MATHEMATICAL MODELING OF FUNCTIONING THE INFORMATION TECHNOLOGY FOR DETECTING THE CARDIAC PACEMAKER DYSFUNCTIONS

Abstract

The development of information technologies for detecting pacemaker malfunction is a priority topic in contemporary science and medicine in the field of cardiology. The development of information technology for recognizing pacemaker dysfunction will help maintain the patient's health in proper condition and prevent complications, which will improve the quality of medical care and increase patient safety. The article presents a mathematical model of the functioning of information technology for recognizing pacemaker dysfunction, which allows formalizing the logic of input data analysis and decision-making, as well as the main functions of information technology for recognizing pacemaker dysfunction. It is based on the collection of multicomponent medical data, its processing using specific algorithms, and decision-making based on logical conditions or intelligent methods. The creation of such a model is the basis for the further implementation of the system in the form of information technology and software that can help doctors quickly and accurately detect malfunctions in implanted devices. In general, the modeling results confirm the feasibility of the chosen approach and demonstrate that the information technology under development is promising for further implementation and practical application in medical diagnostics. The expected practical result is information technology for recognizing pacemaker dysfunction, which works on integrated algorithms for analyzing pacemaker signals based on logical rules, has a convenient and intuitive user interface that provides information about the status of the pacemaker and reports detected anomalies, and provides continuous monitoring and timely notification of potential pacemaker malfunctions. This technology will reduce risks for patients, as it will allow for the timely detection and warning of possible malfunctions in the pacemaker, which, in turn, will reduce the risk of complications and increase the effectiveness of treatment by responding quickly to critical changes in the device's operation.