Issue 3 (197), article 6


Cybernetics and Computer Engineering, 2019, 3(197), pp.

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

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

Orlenko V.L.2, PhD (Medicine), Senior Researcher,
Head of the Department of Scientific-Advisory Department of Ambulatory and Preventive Care
for Patients with Endocrine Pathology

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

Obelets T. A.1,
Junior Researcher of the Department of Mathematical and Technical
Methods Application in Biology and Medicine

1International 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,
40, Glushkov av., Kyiv, 03187, Ukraine

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


Introduction. Modern Diabetes mellitus is dangerous, chronic endocrine disease that originates from the disorder of metabolism, connected primarily with violation of carbohydrate exchange. Providing the necessity of independent self-control of health status of diabetes patients is the urgent problem of present time. The use of information technologies and mobile medicine facilitates enhancing of efficiency of self-control of health status by the patient.

The purpose of the work is to develop a combined information technology to enhance the efficiency of glycemic self-control in case of diabetes at different stages of treatment.

Results. We offer the algorithm of determination of the state of glycaemia regulation system based on the analysis of test results of glucose tolerance and the extended classification scale of glycaemia control (norm, violated tolerance (non-obvious diabetes, latent form), risk zone) that enhances the split ability of standardized methodology and enables timely measures of prophylactic actions to prevent real violations in glycaemia control system. An algorithm is implemented into software for desktops, tablets and mobiles under Android OS.

The developed information technology of decision-making support to choose an adequate mode of activity and meals for patients with diabetes helps to calculate the misbalance between energy gained by chosen menu (by the set of foods and dishes) and energy spent at the different types of the pre-arranged activity (physical, intellectual etc.).

Conclusions. Introduction of the designed algorithm in mobile devices is aimed to facilitate the availability of early diagnostics of violations in carbohydrate regulation system that may assist to reduce risks of emergence of obvious forms of diabetes mellitus. The use in the designed technology the principle of the external combined adjustment, that unites positive features of adjustment by disturbance with adjustment with feedback provides the possibility to enhance efficiency of self-control of the health status for the patient. The technology is implemented for desktops, tablets and mobiles on Android OS and enables access to information for the user with different degree of violation in carbohydrate exchange adjustment — at the state of preambulatory help and during the treatment.

Keywords: information technology, diabetes mellitus, self-control of patient’s health, management principles, M-medicine mobile media: information technology, self-monitoring of patient’s health, management principles, mobile applications.

Download full text!


1 Dedov I.I. Diabetes mellitus is the most dangerous challenge to the world community. Bulletin of the Russian Academy of Medical Sciences. 2012.V.67, no.1, pp.7-13. (In Russian).

2 Jung H.S. Clinical Implications of Glucose Variability: Chronic Complications of Diabetes. Endocrinol Metab (Seoul). 2015, 30(2), pp. 167-74.

3 Dedov I.I., Shestakova M.V., Vikulova O.K., Zheleznyakova A.V., Isakov M.A. Diabetes mellitus in the Russian Federation: prevalence, incidence, mortality, carbohydrate metabolism parameters and structure of hypoglycemic therapy according to the Federal Register of Diabetes Mellitus, 2017 status. Diabetes mellitus. 2018, T.21, no. 3, pp. 144-159. (In Russian).

4 Efimov A.S., Orlenko V.L., Sokolova L.K. Diabetes mellitus and its complications. Journal. pract. doctor. 2003, no 2, pp.34-40. (In Russian).

5 IDF Diabetes Atlas 8th edition 2017 update, URL:

6 Diabetes. WHO 2018. URL:

7 Pankov V.I. Diabetes mellitus: definition, classification, epidemiology, risk factors. International. Journal of Endocrinology. 2013, no. 7 (55), pp. 55-60. (In Russian).

8 Diabetes in Ukraine. “Diaforum 2017”. URL: (In Ukrainian).

9 Shaw J.E., Sicree R.A., Zimmet P.Z. Diabetes Atlas: Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Research and Clinical Practise. 2010, Vol. 87, pp. 4-14.

10 The prevalence of diabetes in Ukraine. URL: (In Russian).

11 Innovative care for chronic conditions. Key elements for action: global report of the world health organization (WHO ,2003). URL: icccrussian.pdf/ua. (In Russian).

12 Inzucchi S.E., Bergenstal R.M., Buse J.B. [et al.] Management of Hyperglycemia in Type 2 Diabetes, 2015: A Patient-Centered Approach: Update to a Position Statement of the American Diabetes Association and the European Association for the Study of Diabetes. Diabetes Care. 2015. Vol. 38, no. 1, pp. 140-149.

13 Whitehead L, Seaton P. Whitehead L, Seaton P. The Effectiveness of Self-Management Mobile Phone and Tablet Apps in Long-term Condition Management: A Systematic Review. J Med Internet Res. 2016. Vol. 18(5):97.

14 Debon R., Coleone J.D., Bellei E.A., De Marchi A.C.B. Mobile health applications for chronic diseases: A systematic review of features for lifestyle improvement. Diabetes Metab Syndr.2019. Vol. 13, no. 4, pp. 2507-2512.

15 Mamedov M.N. Self-monitoring in diabetes: the use of modern technology at home. Medical advice. 2016, no.13, pp.95-98. (In Russian).

16 Dreval A.V., Redkin Yu.A. The role of self-control in the treatment of diabetes. Russian medical journal. 2016, no. 1, pp. 38-40. (In Russian).

17 Balabolkin M.I., Klebanova E.M., Kreminskaya V.M. Treatment of diabetes and its complications (a guide for doctors). Moscow: Medicine, 2005. (In Russian).

18 Samson O.J., Bolshova O.V., Muz V.A. Features of diabetes self-control in children and adolescents. Clinical endocrinology and endocrine surgery. 2010, no. 2 (31), pp.42-47. (In Ukrainian).

19 Report of a seminar on pump insulin therapy. The Russian Diabetic AS-Society (June 23-26, 2012). URL: (In Russian).

20 Dedov I.I., Shestakova M.V., Mayorov A.Yu. Algorithms for specialized medical care for patients with diabetes mellitus. 8th edition. Moscow: UP PRINT, 2017. (In Russian).

21 Karpel’ev V.A., Fedorov E.A., Filippov I. Yu., Shestakova M.V. Intraperitoneal infusion of insulin in diabetes mellitus: Towards an artificial pancreas. Diabetes mellitus. 2015, no. 3, pp.32-45. (In Russian).

22 Riazi H., Larijani B.,Langarizadeh, M. And L. Shahmoradi. Managing diabetes mellitus using information technology: a systematic review. J Diabetes Metab Disord. 2015. Vol. 14, p. 49.

23 Jackson C.L., Bolen S., Brancati F.L., Batts-Turner M.L., Gary T.L. A systematic review of interactive computer-assisted technology in diabetes care: interactive information technology in diabetes care. J Gen Intern Med. 2006. Vol. 21, no. 2, pp.105-110.

24 Saenz A., Brito M., Moron I., Torralba A., Garcia-Sanz E., Redondo J. Development and validation of a computer application to aid the physician’s decision-making process at the start of and during treatment with insulin in type 2 diabetes: a randomized and controlled trial. J Diabetes Sci Technol. 2012. Vol. 6(3), pp. 581-8.

25 Tronko N.D., Halangot N.D. The use of computer systems and information technologies in practical diabetes. Endokrynolohiya. 2001, no. 1, pp.89-94. (In Russian).

26 Marcolino M.S., Maia J.X., Alkmim M.B.M., Boersma E., Ribeiro A.L. Telemedicine application in the care of diabetes patients: systematic review and meta-analysis. Plos One. 2013. Vol. 8(11), e79246.

27 Adaji A., Schattner P., Jones K. The use of information technology to enhance diabetes management in primary care: a literature review. Informatics in Primary Care. 2008, no. 16, pp. 229-37.

28 Siriwardena L.S.A.N., Sudarshana Wickramasinghe W.A, Dussantha Perera K.L, Marasinghe RB, Katulanda P, Hewapathirana R. A review of telemedicine interventions in diabetes care. J Telemed Telecare. 2012, no. 18, pp. 164-168.

29 Chestnov O.P., Boytsov S.A., Kulikov A.A., Baturin D.I. Mobile healthcare: global experience and prospects. Preventative medicine. 2014, no. 17(4), pp 3-9. (In Russian).

30 Bree Holtz, Carolyn Lauckner. Diabetes management via mobile phones: a systematic review. Telemedicine and e-Healt. 2012. Vol. 18, no. 3, pp. 175-185.

31 Faraz S. Ahmad, Thomas Tsang. Diabetes Prevention, Health Information Technology, and Meaningful Use. American Journal of Preventive Medicine. 2013. Vol. 44, no. 4, pp. 357-363.

32 Pradeepa R., Prabu A.V., Jebarani S., Subhashini S., Mohan V. Use of a large diabetes electronic medical record system in India: clinical and research applications. J Diabetes Sci Technol. 2011, no. 5(3), pp. 543-552.

33 World Health Organization. (2011). Use of glycated haemoglobin (HbA1c) in diagnosis of diabetes mellitus: abbreviated report of a WHO consultation.World Health Organization. URL:

34 Lavrenyuk N.V., Kiforenko S.I., Kotova A.B., Ivaskiva E.Yu. Information and computer support for decision-making in the early diagnosis of diabetes. Kibernetika i vycislitelnaa tehnika. 2009, iss. 157, pp. 54-60. (In Russian).

35 Tronko M.D., Efimov A.S., Kravchenko V.Sh., Early diagnosis of diabetes mellitus and its complications. Doctor Info: Health Portal. 2003. URL:http://www/likarsnfo/pro/43480/. (In Ukrainian).

36 Efimov A.S., Karabun P.M., Epshtein E.V. Obesity and diabetes mellitus. Kyiv: Health, 1987. (In Russian).

37 Efimov A.S., Orlenko V.L., Sokolova L.K. Diabetes mellitus and its complications. Zhurn. prakt. likarya. 2003, no. 2, pp. 34-40. (In Russian).

38 The principles of automatic control, their advantages and disadvantages. URL: (In Russian).

39 Turksoy K., Cinar A. Adaptive control of artificial pancreas systems – a review. J Healthc Eng. 2014. Vol. 5(1), pp.1-22.

40 Cobelli C., Renard E., Kovachev B.P. Artificial pancreas: past, present, future. Diabetes. 2011. Vol. 60, pp. 2672-82.

41 Lebedeva O., Lebedev I. Counting calories. URL: (In Russian).

42 Kadomsky Yu. Alphabet of diabetes. Point intensive insulin therapy of insulin-dependent diabetes mellitus. 2018. URL: (In Russian).

43 School of diabetes. Learn to manage diabetes. URL: https: / Russian).

44 On Approval of the Norms of Physiological Needs of the Population of Ukraine in the Basic Nutrients and Energy. Order of 09.03.2017 No 1073 of the Ministry of Health of Ukraine. URL: (In Ukrainian).

Received 19.06.2019