Balakhonova Svetlana Aleksandrovna, Postgraduate student, Penza State University (40 Krasnaya street, Penza, Russia), email@example.com
Bodin Oleg Nikolaevich, Doctor of engineering sciences, professor, sub-department of information-measuring technology and metrology, Penza State University (40 Krasnaya street, Penza, Russia), firstname.lastname@example.org
Ivanchukov Anton Gennad'evich, Postgraduate student, Penza State University (40 Krasnaya street, Penza, Russia), email@example.com
Polosin Vitaliy Germanovich, Candidate of engineering sciences, associate professor, sub-department of physics, Penza State University (40 Krasnaya street, Penza, Russia), firstname.lastname@example.org
Ubiennykh Anatoliy Gennad'evich, Senior lecturer, sub-department of data-computing systems, Penza State University (40 Krasnaya street, Penza, Russia), utolg@.ru
Background. The improvement of technical devices of heart electrophysiological characteristics monitoring has led to an increase in the volume of transmitted data that has defined a need for development of new algorithms of preliminary analysis of electrocardiosignals and elimination of errors when transferring results. The purpose of the work is to substantiate and develop a method to increase heart condition assessment reliability in the “cardiovid”computer diagnostic system on the basis of an entropy-parametrical analysis of electrocardiosignals and channel code demodulation.
Materials and methods. The approaches to monitoring improvement, given in work, are based on methods of statistical processing of quantitative information on heart condition and features of technical realization of the data transmission channel structure in the “cardiovid”computer diagnostic system.
Results. The authors investigated a statistical model of regression for a sorted number of electrocardiosignal countings, based on information processes’ entropy change assessment for a single cardiocycle. The method of channel code demodulation was developed. The researchers calculated statistical parameters of heart electrophysiological characteristics and error detection probability by a channel code. The obtained modeling results confirm an increase of reliability of heart condition assessment when monitoring its electrophysiological characteristics.
Conclusions. The offered methods of improvement of heart electrophysiological characteristics monitoring on the basis of the “cardiovid”computer diagnostic system allow to increase reliability of heart condition assessment and to expand functionality of the classical analysis of electrocardiosignals.
heart, electrophysical characteristics, monitoring, entropy, thermodynamic and information processes, information quantity, probability of detection error, entropy–parametrical potential.
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