DOI: Inventory reference ISSN 1812-7231 Klin.inform.telemed. Volume 9, Issue 10, 2013, Pages 75-78 Author(s) G. B. Shiroky1, A. V. Ilyahinsky1 V. M. Levanov2, I. S. Mukhina2 Institution(s) 1Joint-Stock Company Special Design Bureau "Infotrans", Nizhny Novgorod, Russia 2Nizhny Novgorod State Medical Academy of the Ministry of Health of Russia Article title Dirichlet distribution as a state model of adaptive regulatory systems of the human body in the analysis of heart rate variability Abstract (resume) The aim of newspaper was to explore the possibility of adapting the method of evaluation of the body, based on a quantitative assessment of the entropy processes analysis of heart rate variability. Investigation of heart rate variability to assess the condition of adaptation of the human body in terms of entropy estimate the ratio of processes occurring in the body and controlled by complex processes neuro-endocrine-humoral regulation. For the study was used the method of calculating the ratio of positive and negative with the use of mathematical models for determination unit β-Dirichlet distribution. Models of cardio-ratio comparison was analyzed with the original software. The study was conducted on 58 patients with circulatory disease and 38 healthy subjects. There were significant differences in heart rate variability, particularly in the values of the "coefficient of adaptation". The data obtained can be used to monitor the effectiveness of treatment and rehabilitation of patients with diseases of the circulatory system. Keywords heart rate variability, rhythmocardiography, entropy, adaptation, diseases of the circulatory system References 1. Анализ вариабельности сердечного ритма при использовании различных электрокардиографических систем Р. М. Баевский, Г. Г. Иванов, Л. В. Чирейкин [и др.] Вестник аритмологии. – 2001. – N 24. – с. 65–87. 2. Майоров О. Ю. Применение локального индекса фрактальности для анализа коротких рядов R–R интервалов при исследовании вариабельности сердечного ритма. О. Ю. Майоров, В. Н. Фенченко Клиническая информатика и телемедицина. – 2010. T.6. Вып.7. с. 6–12. 3. Технико-математический контроль кровообращения — состояние и перспективы. Л. А. Бокерия, В. А. Лищук, Д. Ш. Газизова, Л. В. Сазыкина, Г. В. Шевченко. Клиническая информатика и телемедицина. – 2012. T.8. Вып.9. с. 58–72. 4. Государственная программа развития здравоохранения Российской Федерации. [Электронный ресурс]. Режим доступа: https://www.rosminzdrav.ru/health/72 5. Malik M., Bigger J. T., Camm A. J., Kleiger R. E. and oth. Guidelines for Heart Rate Variability: Standards of Measurement, Physiological Interpretation, and Clinical Use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. European Heart Journal. 1996. – N17(3). Р. 354–381. 6. Reliability of heart rate variability measurements in patients with a history of myocardial infarction. R. Maestri, G Raczak, L. Danilowicz [et al.] Clinical Science. – 2009. – N118(3). – Р. 195–201. 7. Yabluchansky N. The heart rate variability (HRV) Point: Counterpoint discussion raises a whole range of questions, and our attention has also been attracted by the topic. N. Yabluchansky, A. Kulik, A. Martynenko. J. Appl Physiol. – 2007. – N 102. – P. 1715. 8. Иляхинский А. В. Середа Ю. С. Статистические модели в задачах зондирования, – Известия ВУЗов, Радиофизика, 1989, т32, 12, С.1502–1505. 9. Середа Ю. С. Проблемы информационно-статистической теории. Космосинформ, 1998. – 121 c. 10. Пригожин И. Введение в термодинамику необратимых процессов. Изд. иностранной литературы, 1960. – 128с. Full-text version http://kit-journal.com.ua/en/viewer_en.html?doc/2013_10/75-78_Levanov_10_color_sc_P.pdf |
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