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Today, one of the most actual problems of cardiology is to obtain comprehensive data in everyday life to determine current cardiac states, including hidden pathologies, their interpretation and analysis. This article proposes a new method for processing measurements obtained during Holter monitoring and using only the value of the intervals between R peaks of ECG. These peaks have the biggest amplitude and their determination does not present technical difficulties. The improved graphical analysis method proposed by the authors, “Speed Spot”, allows to take into account not only the data of heart rate variability, but also includes an integral characteristic of the rate of change of the variability components. The method was used to determine the type of pathology as atrial fibrillation (AF). To confirm the effectiveness of the proposed method for the detection of arrhythmias, the Atrial Fibrillation Database of www.physionet.org was used, containing records of both normal and arrhythmic signals. A comparative analysis of the SS with Poincare clouds for five patients with AF showed that this method is more sensitive and requires less data to determine the controlled cardiovascular state compared to similar ones. The criteria for estimating the degree of HRV (instability) by the “Speed Spot” can be the geometrical dimensions of an ellipse: the length and width and the coordinate of its center. The proposed method, due to the symmetry of the distribution of cloud points with respect to the x-axis, provides more opportunities for use in systems for automatic tracking of heart rate disturbances. Practical application of the method to automatically determine the degree and type of arrhythmia is an object for further research. Further development of the method involves applying it to other types of hidden cardiopathology. |
