Issue 184, article 7


KVT, 2016, Issue 184, pp.84-94

UDC 004.9:61


Zlepko S.M.1, Tymchyk S.V.1, Lepiohina H.S.2

1Vinnytsia National Technical University, Vinnytsia, Ukraine

2Skadovsk Central District Hospital, Skadovsk, Ukraine , ,


Introduction. The current stage of development of health information systems and technology is characterized by the fact that the most frequently used component of their structures is a workstation (AEWP) specialist. AEWPs are integrating with instrumentations and the computing system, ensuring the fulfillment of the set of basic functions. It is essential to reduce the risk by creating a specialized workstation of a neurologist and the development of consultation method.

The purpose is to improve the quality of medical care for children with motor disabilities through the development of a consultation method for the evaluation of the conclusions adopted by the neurologist.

Results. Proposed consultation method for the evaluation of the diagnostic conclusions child neurologist at the ambiguous and threatening situations. The method is based on selecting and evaluating the competence of experts, and then receive their average assessment and group assessment decision.

Conclusions. Thus, the introduction to the AEWP of the doctor-neurologist two circuits decision structure, where the first — is the level of the doctor, and the second — level panel of doctors for real threat of newborn life situations, a systematic approach to the problem of diagnostics and treatment of motor disorders in children in the perinatal period of life has been achieved.

Keywords: automation equipped working place (AEWP), children’s neurologist, a subsystem of decision-making, expert consultation, evaluation matrix, weights

Download full text (ru)!


  1. INTERIN — medical information systems. Group Interin. Available at:
  2. AEWP obstetrician and automation of the women’s clinic. Information Portal «Lektsii.Net». Available at:
  3. Hardware-software complex for assessment of the mother and fetus FS: presentation. Tomsk Polytechnic University. Department of Medical and Industrial Electronics. Available at:
  4. Kobrinskiy B.A. The logic of the argument in making medical decisions. STI, Ser. 2, 2001, № 9, pp. 1–8.
  5. Functions of the medical council, the order of . The legal department “of the Faculty of Medical Law”. LLC “Faculty of Medical Law“. Available at:
  6. Taran T.A. The formalization of the arguments on the basis of reasoning when making decisions in conflict situations. STI, Ser. 2,1998, № 9, pp. 23–33.
  7. Zlepko S.M., Kovalenko A.S., Prudius P.G. Automation equipped working place (for example, AEWP therapist). Proc. of the 3rd International Scientific Conference “Information Technologies and Computer Engineering”, Vinnitsya, 29th –31t May 2012, Vinnitsya : VNTU, 2012, pp. 68–69.
  8. Azarhov O.Yu., Zlepko S.M., Kosmach L.V. Features building strategy “telemedicine consultation” for rehabilitation of patients in residual period. Measuring and computing in technological processes materials. XII International Scientific Conference (3d–8th June 2013, Odessa); Odessa National Academy of Telecommunications named after O.S.Popov, Odesa — Khmel’nyts’kyy: KNU, 2013, P.115.
  9. Azarhov O.Yu., Shtofel D.H., Timchik S.V. et. al. Hardware-software complex “Automated workplace chief doctor”. Information technology, science, engineering, technology, education, health. Abstracts XIX International Scientific Conference in 4 parts, Kharkiv, 15th–17th May 2012, Kharkiv : NTU «KPI», P. III, p. 65.
  10. Zinchenko S.G. The project is a multidisciplinary consulting center in the Donets-Dnieper economic region of Ukraine. Economy: Problems and hopes practices. Interuniversity collection of scientific papers. Dnipropetrovs’k : «Science and education», 2000, Publ.9, pp.66–72.

Received 15.02.2016

Issue 184, article 6


KVT, 2016, Issue 184, pp.72-84

UDC 519.6+612


Grygoryan R.D., Aksenova T.V., Degoda A.G.

Institute of Software Systems of National Academy of Sciences of Ukraine, Kiev, Ukraine , ,

Introduction. A term cardiac hypertrophy (HH) refers to the phenomenon of increasing of the size of the heart, or its separate part. HH’s initiators can be both mechanisms adapting the entire organism to different modes of blood supply and the development of genetic abnormalities. The lack of a clear distinction in understanding mechanisms of these processes creates problems of diagnosis and treatment of pathological HH. In our opinion, a computer modeling of main hemodynamic effects of different forms of HH is able to shed light on mechanisms of HH and help in clarifying of this distinction.

The purpose of this article is to describe a mathematical model (MM) able to simulate basic hemodynamic effects of the adaptive and pathological forms of HH.

Results. MM describes the pumping function of the heart and vascular hemodynamics in a large and small circulations. MM also takes into account the mechanism of baroreflector regulation of the heart and blood vessels. The heart model quantitatively connects the mean values of flow, pressure and blood volume in each ventricle with its end-diastolic elasticity (C) and input blood pressure. The computer simulation showed that changes of central hemodynamics under left ventricle’s pathological hypertrophy can be satisfactorily reproduced via proper decrease of left ventricular parameter C. The adaptive HH is modeled by combining two procedures: i) growth of C of both ventricles of the heart; ii) adequate lowering of the tone of the cardiac sympathetic nerve.

Conclusions. Despite the MM satisfactorily simulates main effects of HH, its several links are still unclear thus the future advanced MM should include humoral, central neural regulator contours, as well as mechanisms providing energy balance both in cardiac myocites and at organism-scale.

Keywords: mathematical model, human cardiovascular system, computer simulation, adaptive hypertrophy, pathology.

Download full text (ru)!


1 Debold E.P., Schmitt J.P., Patlak J.B. et al. Hypertrophic and dilated cardiomyopathy mutations differentially affect the molecular force generation of mouse alpha-cardiac myosin in the laser trap assay. Am J Physiol Heart Circ Physiol, 2007, 293, pp.284–291.

2 Lakdawala N.K., Givertz M.M. Dilated cardiomyopathy with conduction disease and arrhythmia. Circulation, 2010, 122, pp.527–534.

3 Berry J.F., Naseemen R.H., Rothermel B.A. et al.Models of cardiac hypertrophy and transition to heart failure. Drug Discovery Today: Disease Models, 2007, No4, pp. 197–206.

4 Dellefave L., McNally E.M. The genetics of dilated cardiomyopathy. Curr. Opin. Cardiol., 2010, 25, pp.198–204.

5 Moybenko A.A., Dosenko V.E., Parkhomenko A.N. Endogeneous mechanisms of cardiac protection as a basis for therapy of cardiac diseases. Kiev: Naukova Dumka, 2008, 520 p.

6 Rhian T.M. New insights into mechanisms of hypertension // Current Opinion in Nephrology & Hypertension, 2012, 21, Iss. 2, pp. 119–121.

7 Grygoryan R.D. The Energy basis of reversible adaptation. N.Y.: Nova Science, 2012, 254 p.

8 Grygoryan R.D. The energy concept of arterial pressure. Reports of the National Academy of Sciences of Ukraine, 2011, No7, pp. 148–155.

9 Grygoryan R.D. An individual physiological norm: the concept and problems. Reports of the National Academy of Sciences of Ukraine, 2013, No8, pp. 156–162.

10 Grygoryan R.D. The “floating” arterial pressure paradigm. Dusseldorf, Germany. Palmarium Academic Publishing, 2016, 417 p.

Received 12.02.2016

Issue 184, article 5


KVT, 2016, Issue 184, pp.56-72

UDC 004.75+004.932.2:616


Romanyuk O.A., Kovalenko A.S., Kozak L.M.

International Research and Training Center for Information Technologies and Systems of the National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, Kiev, Ukraine , ,


Download full text (ru)!

Introduction. The need of health care institutions in the repeated use of digital medical images by different specialists during patient care and long-term storage for the analysis of diagnostic information determines the relevance of this work.

The purpose of the article is to form technique for adapting the system of transmission and archiving of digital medical images according to the conditions of the health care institution.

Results. Analysis of medical image storage systems to select the specific software implementation according to the requirements of a particular medical institution was held. After testing and validation in working conditions PACS Conquest DICOM has been selected, its functionality has been verified. The technique of adapting the system for transmission and archiving of digital medical images has been developed, which includes an analysis of instrumental studies systems, installation of database components and configuration of PACS Conquest DICOM-server, connecting the instrumental studies systems and organization of access to digital medical images for medical personnel. Testing of the proposed technique was carried out at the National Institute of Cardiovascular Surgery named by N. Amosov.

Conclusion. The possibility of implementation the free and multi-platform storage system with connection of multiple diagnostic systems for efficient analysis of DMC on each workstation and long-term storage DMC is provided as a result of using the proposed technique.

Keywords: digital medical imaging, standard DICOM, long-term storage.


  1. Kamenshchikov A.A. Interoperability in the field of e-health. Information Technologies and Computing Systems, 2009, № 5, pp. 67–71(in Russian).
  2. Robert Hoyt, Nora Bailey, Ann Yoshihashi. Health Informatics: Practical Guide for Healthcare and Information Technology Professionals (5th ed.). New York.:, 2012, 492p.
  3. EN ISO 12052:2011. Health informatics. Digital imaging and communication in medicine (DICOM) including workflow and data management. Available at:
  4. Oosterwijk Herman. DICOM Basics (3rd ed.). O Tech, 2005, pp. 23–28.
  5. Oosterwijk Herman. PACS Fundamentals (2nd ed.). O Tech, 2004, pp. 25–44.
  6. Dreyer K.J., Hirschorn D.S., Thrall J.H. PACS: A Guide to the Digital Revolution. London.: Springer, 2010, 596p., pp.249–269.

Received 15.12.2015

Issue 184, article 4


KVT, 2016, Issue 184, pp.44-56

UDC 681.5


Romanenko V.D., Milyavsky Y.L.

Educational and Scientific Complex “Institute for Applied Systems Analysis” of National Technical University of Ukraine “Kyiv Polytechnic Institute”, Kiev, Ukraine ,

Introduction. Cognitive maps are widely used for modeling large multidimensional systems. These are weighted oriented graphs that represent concepts and relations between them. When external or internal disturbances affect the system impulse process is initiated. It is described by first-order equation in increments of vertices coordinates. A number of articles solved a problem of control in cognitive map’s impulse process by means of control theory methods. But all of them used external control inputs, i.e. resources of the vertices, for this purpose.

The purpose of the article is to develop new method of control where cognitive map’s edges weights are used as controls for impulse process stabilisation.

Results. New method of control of cognitive maps was developed. It is based on varying of the map’s edges weights. It was supposed that some of the vertices may affect other ones in different way, i.e. stronger or weaker. After presenting impulse process model in full coordinates weights increments were added to the difference equation. They were considered as control inputs which were generated according to the control law developed based on quadratic criterion. Stability of the closed-loop system was demonstrated. To verify the results, method was simulated using cognitive map of student’s socio-educational process. Finally we obtained that for stable cognitive map vertices’ coordinates are quickly stabilised at new levels via edges’ weights varying.

Conclusion. Applying the proposed method of control based on weights varying to impulse process of cognitive map allows setting vertices coordinates on desired levels.

Keywords: cognitive map, control law, weights increments, stabilisation at new levels.

Download full text (ru)!


1 Axelrod R. The Structure of Decision: Cognitive Maps of Political Elites. Princeton University Press, 1976, 404 p.

2 Roberts F. Discrete Mathematical Models with Applications to Social, Biological, and Environmental Problems. Englewood Cliffs, Prentice-Hall, 1976, 559 p.

3 Gorelova G.V., Zakharova E.N., Radchenko S.A. Research of semi-structured problems in socio-economic systems. Cognitive approach. Rostov-na-Donu: Publisher RSU, 2006, 332 p. (in Russian).

4 Romanenko V.D., Milyavskiy Y.L. Stabilizing of impulse processes in cognitive maps based on state-space models. System Research & Information Technologies, 2014, No1, pp. 26–42 (in Russian).

5 Romanenko V.D., Milyavskiy Y.L., Reutov A.A. Adaptive Control Method for Unstable Impulse Processes in Cognitive Maps Based on Reference Models. Journal of Automation and Information Sciences, 2015, No 2 pp. 35–45 (in Russian).

6 Romanenko V.D., Milyavskiy Y.L. Coordinates ratio control for cognitive model of a complex system under unstable impulse process. System Research & Information Technologies, 2015, No1, pp. 121–129 (in Russian).

7 Romanenko V.D., Milyavskiy Y.L. Impulse processes stabilisation in cognitive maps of complex systems based on modal state controllers. Kibernetika i vycislitel’naa tehnika, 2015, No179, pp. 43–55 (in Russian).

8 Romanenko V.D., Milyavskiy Y.L. Adaptive coordinating control of interacting cognitive maps vertices’ ratios in impulse mode. System Research & Information Technologies, 2015, No3. pp. 109–120 (in Russian).

Received 24.03.2016

Issue 184, article 3


KVT, 2016, Issue 184, pp.25-44

UDC 002.53:004.8


 Vovk M.I., Galyan Ye.B.

International Research and Training Center for Information Technologies and Systems of National Academy of Sciences of Ukraine and Ministry of Education and Science of UkraineKiev, Ukraine ,


Introduction. Intelligent control is a function of organized systems, situationally adapted to provide for the operation to be constant. Main mechanisms for constant operation of biological systems are adaptation and homeostasis. We must keep in mind these mechanisms while designing biotechnical systems for control, maintenance or restoration of motor functions, damaged by pathology, as well as remember that speech movements are a type of voluntary movements.

The purpose is to develop information-structural and structural-functional models for organization of intelligent fine motor hand movements control to restore speech.

Methods. information — structural modeling, structural-functional modeling, first-order predicate logic, Unified Modeling Language.

Results. In this article we present information-structural and structural-functional models of intelligent hand movements control organization to restore speech for patients after the stroke (hemiparesis, motor aphasia, motor-sensory aphasia). The main components of the biotechnical system that organizes intelligent control are electronic devices for motor control TRENAR and PC with software-based information component. Its structural-functional model is described. The organism’s reserves activation to restore homeostasis of fine motor hand movements and speech realization is the final goal of control. Adequacy is considered as the best criterion for individual choice of control actions parameters and topology of their application. It is shown how different methods, training programs, and a set of training movements allow us to organize personally oriented situational control / training of hand movements for speech rehabilitation. The method for determining the combination of personal training options for hand and finger movements on the basis of production approach is developed. The software implementation of the method in the form of reduced expert system is described.

Conclusion. The main features of intelligent control organization are the assistance of situational goal to the final goal of control and knowledge-based control.

Keywords: intelligent control, adaptive control, homeostasis, organization, hand movements, speech restoration, modeling, computer complex, electronic devices, information component, production approach, reduced expert system.

Download full text (ru)!


  1. Nefedov V.P. Homeostasis at different levels of biological systems. Novosibirsk: “Nauka”. Siberian branch, 1991, 232 p. (in Russian).
  2. Romanov S.P. Neurophysiological mechanisms of motor functions homeostasis : thesis. Doctor in Biology: specialty. 03.00.13. St. Petersburg, 1989, 443 p. (in Russian).
  3. Vovk M.I. Biological and biotechnical system as a purposeful. Control System and Computers, 2005, № 3(197), pp.16–24 (in Russian).
  4. Vovk M.I. Bioinformatic technology of movements control as the direction of biological and medical cybernetics. Kibernetika i vyčislitelʹnaâ tehnika, 2013, № 174, pp. 56–70. (in Russian).
  5. Kadukov А.S., Chernikova L.A., Shakhparonova N.V. Rehabilitation of neurological patients Chapter 16. Speech disorders. М.: “MEDpress-inform”, 2008, pp. 369–384. (in Russian).
  6. Krakauer JW Arm function after stroke: from physiology to recovery. Semin Neurol. 2005 Dec; 25(4) — p. 384-395. (in English)
  7. Vovk M.I, Galyan Ye.B., Pidoprigora E.N., e.a. Sposib likuvannya movnukh porushen’ [The way to treat speech desorders]. Patent UA, A61N 1/36, no. 111388, 2016. (in Ukrainian).
  8. Vovk M.I., Galyan Ye.B. Restoring of motor component of speech based on muscle movement control. Theoretical grounding. Kibernetika i vyčislitelʹnaâ tehnika, 2012, № 167, pp.51–60. (in Russian).
  9. Vovk M.I., Galyan Ye.B. Pesonalized Biotechnical system to restore speech. Kibernetika i vyčislitelʹnaâ tehnika, 2015, №179, pp. 5–19. (in Russian).
  10. Gritsenko V.І., Kotova A.B., Vovk M.I., Kozak L.M. Information technology in biology and medicine. Lectures: Tutorial. Part 3 Biotechnological systems theory and its application, pp.285–340, Kyiv: Nauk. Dumka, 2007, 381 p. (in Ukrainian).
  11. Koltsova М.М. Motor activity and development of the child’s brain functions. Мoscow: “Pedagogika”, 1973, 143 p. (in Russian).
  12. Varejkin Yu.P., Lastivka O.D., Lauta A.D. The formalization of medical information for automated solving the problem of treatment appointment. Medical and Biological Informatics: collection of scientific papers / the Editorial.: Amosov N.М. and etc. Kiev: VM Glushkov Institute of Cybernetics of NAS of USSR, 1967, pp. 68–71 (in Russian).
  13. Prodeus A.N. Zakhrabova E.N. Expert systems in medicine. Kyiv: “VEK+”, 1998, 320 p. (in Russian).
  14. Solodovnikov I. V., Rogozin O.V., Pashchenko O.B. Decision theory: Tutorial. Moscow: Publishing house of the MSTU. Bauman, 2006. 52 p. (in Russian).
  15. Belova А.N., Shchepetova O.N. Scales, tests and questionnaires in medical rehabilitation: a guide for physicians and researchers. Мoscow: “Antidor”, 2002, 440 p. (in Russian).
  16. Vovk M.I., Peleshok S.R., Galian Ye.B. The method of assessment of motor and sensory speech disorders. Collected papers of scientific-information center “Knowledge” based on XІ International correspondence scientific-practical conference: «The development of science in the XXI century» part 3. Kharkiv: collected papers. D, 2016, pp. 70-76. (in Russian).

Received 15.03.2016

Issue 184, article 2


KVT, 2016, Issue 184, pp.8-25

UDC 681.3.06.14


Fainzilberg L.S.1, Soroka T.V.2

1International Research and Training Center for Information Technologies and Systems of National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, Kiev, Ukraine

2National Technical University of Ukraine “Kiev Polytechnical Institute”, Kiev, Ukraine ,

Introduction. The diseases of cardiovascular system lead in the structure of morbidity. The absence of timely treatment leads to severe complications, invalidity and death of the patient. Only preserving medicine can radically change this situation. Fasegraphy is one of perspective directions in cardiology, that allows even by simplified way of ECG registration to detect early signs of disease development.

Purpose. The development of method of fasegraphy for building of complex telemedicine system for mass prophylactic examinations based on client-server architecture and realization of mobile applications for patients and physicians in Android environment is proposed.

Methods. The portable sensor is used for registration of ECG signal, that provides the transfer of digital data through Bluetooth to the patient’s application. The application provides preprocessing of signal, the control of dosed exercise, stress and transfer data to server. The client’s applications are developed in a java programming language version 7 together with Android sdk. The software of server is written in Java version 8 in conjunction with frameworks Spring 4.3 for REST API and Hibernate 5.1 as ORM. The database is based on MySql 5.5.

Results. The server software provides automatic selection of ECG with atypical cycles for which the physician must pay attention primarily. The algorithm of selection is based on the analysis of ordered Hausdorff distances between trajectories of cycles on the phase plane. When the information about detection of atypical cycles is received, the physician may view ECG, perform additional analysis those ECGs and send appropriate recommendations to patient.

Conclusions. Client-server organization of interaction of physician and patient increases the effectiveness of screening surveys and optimizing time spent by a doctor on the medical services to their patients.

Keywords: client-server system, fasegraphy, distant monitoring, atypical cycles of ECG.

Download full text (ru)!


1 Cassar A., Holmes D.R., Rihal C.S. et al. Chronic coronary artery disease: diagnosis and management. Mayo Clin. Proc., 2009, Vol. 84, No 12, pp. 1130–1146.

2 Basso C., Corrado D., Thiene G. Prevention of sudden cardiac death in the young and in athletes: dream or reality? Cardiovascular Pathology. 2010, Vol. 19, No 4, pp. 207–217.

3 Thaulow E., Erikssen J., Sandvik L. et al. Initial clinical presentation of cardiac disease in asymptomatic men with silent myocardial ischemia and angiographically documented coronary artery disease (the Oslo Ischemia Study). American Journal of Cardiology, 1993, Vol. 72, No 9, pp. 629–633.

4 Gozhenko A., Kulbida M., Kochetov A. Preventive medical science strategy — a way to improve the efficiency of health care. Journal of National Academy of Sciences of Ukraine, 2011, No 12, pp. 64–69 (in Ukrainian).

5 Solopov V., Sadykova A., Fedoseyeva T. Restrictions of automatic analysis of computer. Kazansky Medical Journal, 2012, T.93, No 4, pp. 687-691 (in Russian).

6 Lourenco A. Unveiling the Biometrical Potential of Finger-Based ECG Signals. Computational Intelligence and Neuroscience, 2011, Vol. 2011, pp. 1–8.

7 Grier J.W. Comparison and review of portable, handheld, 1-lead/channel ECG / EKG recorders. Available at

8 Fainzilberg L.S. Computer diagnosis of the phase portrait of the electrocardiogram. Kiev: Osvita Ukrainy, 2013, 191 p. (in Russian).

9 Fainzilberg L.S. ECG Averaging based on Hausdorff Metric. International Journal of Biomagnetism, 2003, Vol. 5, No 1, pp. 236–237.

10 Fainzilberg L.S. Nowa metoda interpretacji zapisu EKG w balaniach skriningowych oraz w opiece domowej. Zdrowie publiczne (Public Health), 2005, Vol. 115, No 4, pp.458–464.

11 Matjaz Perc. Nonlinear time series analysis of the human electrocardiogram. European Journal of Physics, 2005, No 26, pp. 757–768.

12 Minina E.H., Fainzilberg L.S. Analysis of the functional condition of the cardiovascular system of the combination of features of the phase portrait of single-channel ECG. Russian Cardiology Journal, 2015, No 12 (128), pp. 7–13 (in Russian).

13 Fainzilberg L.S. Information signal processing technology complex shape. Theory and practice. Kiev: Scientific Thought, 2008, 333 p. (in Russian).

14 Gritsenko V.Y., Fainzilberg L.S. Information technology of FAZAGRAF for the integrated estimation of the cardiovascular’s system condition on phase portrait of electrocardiogram. Doctor and Information Technology, 2013, No 3, pp.52–63 (in Russian).

15 Vishnevsky V.V. Grid-based system for mass storing and and processing of digital electrocardiograms. Ukrainian Journal of Telemedicine and Medical Telematics, 2013, E. 11, No 1, pp. 202–208 (in Russian).

16 Fainzilberg L.S., Soroka T.V. The development of telemedicine systems for remote monitoring heart activity based on the method of fasegraphy. East European Journal of advanced technologies, 2015, No 6/9(78), pp. 37–46 (in Russian).

17 Kaya Y., Pehlivan H. Classification of Premature Ventricular Contraction in ECG. International Journal of Advanced Computer Science and Applications, 2015, Vol. 6. No 7, pp. 34–40.

18 Goldberger A.L. Fractal mechanisms in the electrophysiology of the heart. IEEE Eng. Med. Biol., 1992, No 11, pp. 47–52.

19 Genkin A.A. The new information technology of medical data analysis. SPB: Polytechnic, 1999, 192 p. (in Russian).

Received 28.04.16