Issue 183, article 1

Fainzilberg Leonid S., Dr of Engineering, Chief Researcher of Data Processing Department of International Research and Training Center for Information Technologies and Systems National Academy of Sciences of Ukraine and of Ministry of Education and Science of Ukraine, av. Acad. Glushkova, 40, Kiev, 03680.

Orikhovska Kseniya B.,Postgraduate (PG) of International Research and Training Center for Information Technologies and Systems National Academy of Sciences of Ukraine and of Ministry of Education and Science of Ukraine, av. Acad. Glushkova, 40, Kiev, 03680,

Vakhovskyi Ivan V., Student of National Technical University of Ukraine “Kiev Polytechnical Institute”, av. Pobedy, 37, Kiev, 03056,

ASSESSMENT OF CHAOTIC FRAGMENTS’ SHAPE OF THE SINGLE-CHANNEL ELECTROCARDIOGRAM. Kibernetika i vyčislitel’naâ tehnika, 2016, issue 183, pp.4-24.

Introduction. Building an effective information technology (IT), which provides chaotic assessment of the electrocardiogram (ECG) fragments’ shape, has both cognitive and practical importance. Therefore, the problem of developing methods and computer tools that provide assessment not only by the rhythm of the heart, but also on other parameters of ECG that have diagnostic value is relevant.

The purpose of the article is to propose instrumental system for the study of single-channel ECG elements shape chaoticity, based on the various entropy assessments and make a comparative analysis of these estimates in the model and the real data.

Methods. The proposed instrumental system based on the national portable electrocardiograph FAZEGRAF® with the original finger electrodes sensor, which can record the ECG from the first standard lead. In addition to determining the chaoticity of parameters, that characterize the shape of the main elements of the ECG, also estimating the diagnostic features chaoticity. Introduced a number of improvements in the considered methods which determine the signal chaoticity degree. In particular, an original evaluation algorithm for permutation entropy evaluating that can automatically identify 5 classes of patterns is proposed.

Results. Processing of model and real data showed that the computing algorithms implemented in IT allow to adequately assessing the degree of signals chaoticity. Based on the parameters chaotic assessment, that carry information about the ECG elements shape, diagnostically important subtle signal differences in healthy and sick patients, as well as significant differences in parameters of the ECG elements shape chaoticity in people with varying degrees of organism fitness were found.

Conclusions. Instrumental system provides the convenience of experimental studies with searching for new biomarkers of cardiac abnormalities and evaluation of organism adaptation capabilities.

Keywords: heart rate, the entropy of the process, synergy, shape of ECG fragments.

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Received 08.12.2015