Algorithm for Automatic Recognition of Cardiac Arrhythmias

Problem statement: Cardiovascular diseases currently remain one of the leading causes of death. It is important to monitor the state of the cardiovascular system in early stages of pathology in order to diagnose these diseases in a timely manner. A special place is occupied by various arrhythmias among diseases of the cardiovascular system. The most common ones of various arrhythmias are extrasystoles. Ventricular extrasystoles are considered the most life-threatening among extrasystoles. In order to diagnose ventricular extrasystoles at an early stage of their development, it is necessary to process and analyze large amounts of electrocardiographic data. In this regard, the development and software implementation of algorithms for automatic recognition of ventricular arrhythmias based on electrocardiographic data through modern computer technologies is an urgent task. Work objective is developing an algorithm for automatic recognition of ventricular arrhythmias and its software implementation. Results: An algorithm for automatic recognition of ventricular extrasystoles, which is characterized by simplicity of implementation and minimal requirements for computing resources, has been developed. At the same time, high values of sensitivity and specificity are maintained for ECG signals with single ventricular extrasystoles. The algorithm is implemented in the LabVIEW software environment and tested using ECG files taken from international databases on cardiac arrhythmias, as well as using stimulated ECG signal models. Practical significance: The developed algorithm can be used in automatic processing and analysis of long-term ECG recordings and recognition of ventricular arrhythmias.