Big Data and real-time examination of patients with atrial fibrillation

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Snitser Anatoly Arnoldovich, Zakharyan Elena Arkadyevna, Shvets Yuri Yurievich, Klyueva Darya Vladimirovna, Molchanenko Violetta Andreyevna


The capacity and throughput of medical centers is often insufficient to monitor patients with cardiovascular insufficiency. Modern mobile ECG systems, digital technologies, and intellectualization help in such tasks by automatically processing and analyzing (without additional resources) the patient's condition for any place, channel, or time. Big Data, Data Mining allow us to explore hidden connections in a variety of medical data, giving an opportunity to analyze data with a volume several orders of magnitude higher. In the article, based on the methods and principles of system analysis, statistical and mathematical analysis, the evolutionary potential of Big Data is analyzed, the real-time examination of patients with atrial fibrillation and plethysmogram curves is considered, the statistical intelligent analysis of plethysmogram wave peaks is implemented with the use of a defibrillator-monitor, the Statistica 10.0 package.

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