Issue 3 (193), article 5


Kibern. vyčisl. teh., 2018, Issue 3 (193), pp.

Kiforenko S.I.1, DSc (Biology), Senior Researcher,
Leading Researcher of Dep. of Application Mathematical
and Technical Methods in Biology and Medicine

Hontar T.M.1, PhD (Biology), Senior Researcher,
Dep. of Application Mathematical and Technical Methods in Biology and Medicine

Ivaskiva K.Y.2, PhD (Medicine), Senior Researcher,
Scientific-advisory of Dep. of Ambulatory and Preventive Care for Patients with Endocrine Pathology

Obelets T.A.3, Computer Systems Analyst

1 International Research and Training Centre for Information Technologies
and Systems of the National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, Glushkov ave., 40, Kyiv, 03187, Ukraine

2 State Institution “V.P. Komisarenko Institute of Endocrinology and Metabolism of NAMS of Ukraine”, 69, Vyshgorodska St., Kyiv, 04114, Ukraine

3 National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Peremogy av. 37, Kyiv, 03056, Ukraine


Introduction. Somatic health is the most important component of human health. It is the physical status that has a responsible role in the material and energy provision of the functioning of the physiological systems of the organism and their maintenance within the boundaries of the homeostatic norm. Emphasis on the motivation and self-control of their health, on an adequate orientation in the use of modern health-saving technologies is relevant.

The purpose of the article is to create a decision support system for increasing awareness of the health status and improve the efficiency of correcting the state of somatic health by using modern computer and mobile technologies.

Methods. The paper describes the information technology of quantitative assessment and correction of a person’s physical health, which is based on the information-structural model of a person’s physical health. A software-algorithmic complex for use in personal computers and mobile applications to support decision-making in the selection of recreational activities has been developed.

Results. The information structure of physical health was developed from the viewpoint of management theory, taking into account the subjective-objective aspects of evaluation and the multidimensionality of the research object. To support decision making in assessing health status and selecting preventive measures, a set of computer programs “HEALTH-ENERGY BALANCE ” has been developed. The basis of the complex is the modules “Early Diagnosis” — for assessing the condition and “Energobalance” — to support decision making when choosing a balanced diet, adequate activity and daily energy costs. Given the current trends in the development of the mHealth industry, this software is adapted for use in mobile devices.

Conclusion. The developed technology allows, using non-invasive techniques, to quantify the state of physical health. Depending on the position of the evaluation criterion on the diagnostic scale, the user is given the opportunity to choose the appropriate recreational techniques and minimize the mismatch between the energy value of the food ration and energy expenditure in selecting the activity mode. Implementation of the developed algorithms in mobile Android applications to the smartphone increases the effectiveness of supporting independent decision-making when organizing the life of the user.

Keywords: somatic health, automated information technology, objectively-subjective evaluation, software, mobile applications.

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1.    Health Ukrainians: frightening statistics. URL: (Last accessed: 08.02.18.) (in Russian)
2.    Nazarova E.N, Zhilov Yu. D. Fundamentals of a healthy lifestyle. Moscow: Academy, 2013. 256 p. (in Russian)
3.    Apanasenko G.L. Individual health: theory and practice of management, information aspects. Meditsinskaya informatika i inzheneriya. 2009. № 4. P. 61–64. (in Russian)
4.    Dartau L.A, Misernitsky Yu.L., Stefanyuk A.R. Human health and quality of life: problems and management features. Moscow: SINTEG, 2009. 400 p. (in Russian)
5.    Chestnov OP, Boytsov S.A., Kulikov A.A., Baturin D. Mobile health: world experience and perspectives. Profilakticheskaya meditsina. 2014. Vol. 17. №. 4. P. 3–9.
6.    Apanasenko G.L. Valeology: first results and immediate prospects. Teoriya i praktika fizicheskoy kul’tury. 2001. № 6. P. 2–8. (in Russian)
7.    Ivanova S.S, Stafeeva A.V. Substantial aspects of physical, mental and social health and the possibility of forming their harmonious correlation. Fundamental’nyye issledovaniya. 2014. No. 11 (part 12). P. 2729–2733. (in Russian)
8.    Gritsenko V.I, Vovk M.I., Kotova A.B. Bioecomedicine. Kiev: Nauk. dumka, 2001. 318 p. (in Russian)
9.    Gritsenko V.I., Kotova A.B., Kiforenko S.I. et al. Information technology in biology and medicine. Course of lectures: the textbook. Kiev: Nauk. dumka, 2007. 382 p. (in Ukrainian)
10.    Pustovoit O.G., Kotova A.B, Kiforenko S.I. Information technology research and management of human physical health. Upravlyayushchiye sistemy i mashiny. 2010. N 3. P. 70–77. (in Russian)
11.    Kotova A.B., Belov V.M. Human Health: Challenges, Methods, Approaches. Kiev: Nauk. dumka, 2017. 132 p. (in Ukrainian)
12.    Kiforenko S.I., Kotova A.B. Multidimensionality as a basis for the systemic evaluation of health. Kibernetika i vyčislitel’naâ tehnika. 2006. Iss. 150. P. 60–69. (in Russian)
13.    Cooper K. Aerobics for well-being [2 nd ed. additional, revised]. Moscow: Fizkultura i sport, 1989. 224 p. (in Russian)
14.    Apanasenko G.L. Diagnosis of individual health.Sovremennyye reabilitatsionnyye tekhnologii. 2012. № 8. P. 64–69. (in Russian)
15.    Landa B.H. Methods for the integrated assessment of physical development and physical fitness: Textbook. allowance. Moscow : Sovetskiy sport, 2011. 348 p. (in Russian).
16.    Nikiforov G.S. Psychology of professional health. St. Petersburg: Rech’, 2006. 408p. (in Russian).
17.    Cooper’s motor tests. URL: (Last accessed: 31.01.18.)
18.    Baevsky R.M. Assessment of adaptive capabilities of the body and the problem of restorative medicine. Vestnik vosstanovitel’noy meditsiny. 2004. № 2. P. 18–22. (in Russian).
19.    Belov V.M., Kotova A.B., Dubovenko M. N., Kiforenko S.I. Computer program “System of express diagnostics of a state of health”: a certificate of registration of copyright law on the work №37242, Ukraine. — 04/03/2011.
20.    Kiforenko S.I., Kravchenko V.V. Information and technological aspects of monitoring and evaluation of physical health. Visnyk KNU. Seriya Kibernetyka. 2014. №1(14). P. 27–32. (in Russian).
21.    Makaricheva V.V. Computer decision support system for the integrated assessment of physical health. Visnyk KNU. Seriya Kibernetyka. 2016. №1(164). P. 15–20. (in Russian).
22.    WHO. Diet, nutrition and the prevention of chronic diseases (report of the joint WHO – FAO expert consultation). 2003. 196 p. (in Russian).
23.    WHO. Resolutions and reports. Global Strategy on Diet, Physical Activity and Health (WHA57.17, 2004). 2004. 18 p. (in Russian).
24.    On Approval of the Norms of Physiological Needs of the Population of Ukraine in the Basic Nutrients and Energy. Order of 09.03.2017 № 1073 of the Ministry of Health of Ukraine. URL: (Last accessed: 26.01.18)
25.    Energy costs for various activities. Guidelines. URL: (Last accessed: 01.03.18)
26.    WHO. Innovative methods of care for chronic conditions: the main elements for action (global report 2002). 2002. 92 p. (in Russian).
27.    Kiforenko S.I., Kotova A.B., Lavrenyuk N.V., Ivaskiva E.Yu. Diagostics of diabetes mellitus. Progressive information technology. Upravlyayushchiye sistemy i mashiny. 2015. № 4. P. 67–71. (in Russian).

Recieved 03.06.2018

Issue 1 (187), article 6


Kibern. vyčisl. teh., 2017, Issue 1 (187), pp.80-96

Kiforenko S.I., leading researcher at the Department of mathematical and technical methods in biology and medicine

International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and Ministry of Education and Science of Ukraine,
av. Acad. Glushkova, 40, Kiev, 03680, Ukraine


Introduction. In recent years there have been fundamental changes in the understanding of the requirements for the possibilities of using mathematical models. Now the model can not be seen as a self-contained object of research but as well as an element of integrated formulation of task management. Thereby it becomes information technology tool to solve this problem. It is possible to use the simulation results not only to solve control problems, but also for wider use — in the development of information systems support decision making in medical treatment and diagnostic process.

The purpose of the article is to summarize the experience in the development of hierarchical modeling technology of the system regulation of blood glucose using models different levels of complexity in a single technological cycle.

Methods. Structural and functional modeling, hierarchical modeling, methods of synthesis of mathematical models, methods for parameter identification and verification of models, methods of control theory.

Results. On the example of the regulation of blood glucose system is developed hierarchical modeling technology, based on the simultaneous use in a single technological cycle mathematical models of various levels of complexity: MAX, MIDI, MINI. The first type — a high level of complexity of the model — MAX-model — the closest to the modern ideas about the laws regulating the functioning of the system — used to simulate the object of research. The second type — these are more simple models of research object — MIDI model, — are used for the synthesis of control actions and fulfil the prediction function. The third type — the models are still at a lower level of complexity. — MINI model. Differential equations of these models have the analytical solutions and therefore it can possibly to calculate the control actions and functions of the forecast for calculation formulas.

Conclusions. This arrangement extends the range of simulation tasks and allows to analyze, at the stages of theoretical research and pre-clinical testing, the various aspects of the synthesis and test the effectiveness of the control algorithms that are relevant in diabetology.

Keywords: hierarchical simulation, system regulation of blood glucose, control algorithms, preclinical testing.

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1 Karpel`ev V.A., Fylyppov Y.I., Tarasov Yu et al. Mathematical modeling of blood glucose regulation system in patients with diabetes. Herald of the RAMS. 2015. Vol. 70. No. 5. P. 549–570. (In Russian).

2 Gomenyuk S.M., S.A. Emelyanov, Karpenko A.P., Tchernetsov S.A. Review of methods and forecasting systems of optimal insulin doses for patients with type 1 diabetes. Information tehnologies. 2010; (3). P. 48–57. (In Russian).

3 Cobelli C., C. Dalla Man, G. Sparacino et al. Diabetes: models, signals, and control. IEEE reviews in biomedical engineering. 2009. No. 2. P. 54–96.

4 Palumbo P., S.Ditlevsen, A.Bertuzzi, A. De Gaetano. Mathematical modeling of the glucose–insulin system: A review. Mathematical biosciences. 2013. Vol. 244. No. 2. P. 69–81.

5 Nefedov V.P., Jasaitis A.A., Novoseltsev V.N. et al. Homeostasis at different levels of biological systems organization et al. Novosibirsk: Nauka, 1991. 232 p. (In Russian)

6 Drishel G. Regulation of blood sugar level. Regulatory processes in biology. M.: Nauka, 1960. P. 63–85 (In Russian).

7 Goldman S. On the question of cybernetic aspects of homeostasis. Self-organizing systems. Moscow: Nauka, 1964. P. 40–62. (In Russian).

8 Bolie V. Coefficients of normal blood glucose regulation. J. Appl. Physiol. 1961. Vol. 16. P. 783–788.

9 Ackerman E., Gatewood L.C., Rosevear J.W., Molnar D.G. A mathematical model of the glucose-tolerance test. Phys. Med. Biol. 1964. Vol. 9 P. 203–215.

10 Segre C., G.L. Turco, G. Vercelione. Modelling blood glucose and insulin kinetics in normal? Diabetics and obese subjects. Diabetes. 1973. Vol. 22. P. 94–

11 Bergman E.E., J. Urquhart. The pilot giand approach to the study of insulin secretory dynamics. Recent Progr. Hormone Res. 1971.Vol. 27. P. 583–

12 Grodsky C.N., D. Curry, H. Landahi, L. Bennett. Purther studies of the dynamics aspects of insulin release in vitro, with evidence for the two-compartmental storage system. Acta diabet. Latina. 1969. Vol. 6, Suppl. No 1. P. 554–579.

13 Biekomeditsina. Single Information Space / Ed. V.I. Gritsenko. Kiev: Nauk. Dumka, 2001. 318 p. (In Russian).

14 Antomonov Y.G., Kiforenko S.I., Mikulskaya I.A., Parokonnaya N.K. The mathematical theory of blood glucose system. Kiev: Nauk. Dumka, 1971. 82 p. (In Russian)

15 State and prospects of development of science in Ukraine (group of authors). Kiev: Nauk.dumka, 2010. 1008 p. (In Russian)

16 Antomonov Yu., S. Kiforenko, B. Allamiarov et al. Theoretical investigation of carbohydrate and lipometabolism systems and use of simplified mathematical models for control. Kybernetes. 1977. Vol.6. No 4. P. 297–303.

17 Allamiyarov B.U., Kiforenko S.I. Experimental study and mathematical modeling of some indicators of carbohydrate and fat-lipid metabolism dynamics in a single injection of adrenaline. Mathematical models in biology. Kiev: Inst. of Cybernetics, 1974. P. 17–24 (In Russian).

18 Allamiyarov BU, Khamdamov R. Identification of the mathematical model of the level of glucose and blood free fatty acids control in diabetes. Proc. of the Academy of Sciences of the Uzbek SSR, Ser. tehn. Science, 1982. No 4. P. 38–43 (In Russian).

19 Cobelli, C. Federspil, G. Pacini et al. An integrated mathematical model of the dynamics of blood glucose and its hormonal control. Math. Biosci. 1981. Vol. 5. P.27–60.

20 Dartau L.A., Orkina E.L., Novoseltsev V.N., Sklyanik A.L. Carbohydrate metabolism: Integral models. Engineering physiology and modeling of the body’s systems. Novosibirsk: Nauka, 1987. P. 54–69 (In Russian)

21 Albisser A.M., Y Y. Amasaki, O.Broekhuyse, I. Tiran. Hypercomplex models of insulin and glucose dynamics: do they predict experimental results. Ann. Biomed. Engin. 1980. Vol. 8. P.539–557.

22 Cobelli C., E. Ruggari. Evaluation of portal/periphersi route and of algoritme for insulin delivery in the closed-loop control of glucose in diabetes. A modeling etudy. IEES Tranzasct. Biomed. Eng. 1983. Vol. 30. P. 93–103.

23 Cobelli C., A. Mari. Control of diabetes with artificial systeme for insulin delivery algorithm independent limitations revealed by a modeling study. IEEE Transact. Biomed. Eng. 1985. Vol. 32. P. 840–845.

24 Cobelli C. Modelling and identifications of endocrine-metabolic systems. Theoretical aspects and their importance in practice. Math. Biosci. 1984. Vol. 72. No 2. P. 263–289.

25 Lapta S.I., S.S. Lapta. Functionally-phenomenological model of oral glucose-tolerance test. Problems of bionics. 2000. No 52. P. 52–57 (In Russian).

26 Lapta S.S., L.A. Pospelov, O.I. Solovyov. Computer early diagnosis of diabetes by methods of mathematical modelling. Vestn. NTU “KhPI”. 2014. No36 (1079). P. 55–61 (In Russian).

27 E.I. Sokol, S.S. Lapta. Mathematical model of carbohydrate metabolism regulation Vestn. NTU “KhPI”. 2015. No33 (1142). P. 152–157 (In Russian).

28 Zhevnin A.A., Kolesnikov K.S., Kryschenko A.P., & Toloknov V.I. Synthesis of Terminal Control algorithms based on the concepts of inverse dynamics problems (review). Proc. AN SSSR. Tech. Cybernetics. 1985, No 4. P. 180–188 (In Russian).

29 Glushkov V.M., Amosov N.M., Antomonov Yu. et al. Methods of mathematical biology. V. 5. Methods of analysis and synthesis of biological control systems. Kiev: Vishcha shk., 1983. 272 p. (In Russian).

30 Novoseltsev V.N. Mathematical modeling in the age of computers. Moscow: Inst. probl. upr. RAN, 2002 (In Russian).

31 Kiforenko S.I. Conceptual bases of simulation study: the system of carbohydrate metabolism — the external control system. Cybernetics and Computer Science. Iss. 110. 1997. P. 64–71 (In Russian).

Recieved 30.12.2016