Issue 4 (210), article 4

DOI:https://doi.org/10.15407/kvt210.04.060

Cybernetics and Computer Engineering, 2022, 4(210)

FAINZILBERG L.S., DSc (Engineering), Professor,
1Chief Researcher of the Intelligent Automatic Systems Department,
2Professor of the Department of Biomedical Cybernetics
https://orcid.org/0000-0002-3092-0794
e-mail: fainzilberg@gmail.com

1International Research and Training Center for Information Technologies and Systems of the National Academy of Sciences of Ukraine and the Ministry of Education and Science of Ukraine,
40, Acad. Glushkov av., Kiyv, 03187, Ukraine

2National Technical University of Ukraine “Ihor Sikorsky Kyiv Polytechnic Institute»
37, Peremogy av., Kiyv, 03056, Ukraine

MOBILE INFORMATION TECHNOLOGY FOR ASSESSING THE ADAPTATION CAPABILITIES OF THE HUMAN BODY UNDER CONDITIONS OF INCREASED LOADS

Introduction. An important role in assessing the body’s adaptive reserves under conditions of physical and emotional stress is played by information obtained with the help of special tests. Such tests should be convenient enough to quickly obtain the result, including at home and in the field.

The purpose of the paper is to develop the principles of building mobile IT for the operational assessment of the adaptive capabilities of the human body in the field and at home and the implementation of IT on a smartphone.

Methods. To assess tolerance to physical and emotional stress, a cognitive graphical image is constructed that integrally characterizes the regulatory patterns of changes in the physiological parameters of the heart rate, calculated in three states: at rest, at the height of the load and during restitution.

Results. It is shown that reliable information about the pulse wave (finger photoplethysmogram) during testing can be obtained using the built-in camera of a smartphone without additional technical means based on the developed original computational procedures that provide for the selection of reliable and unreliable cycles. To manage the physical load on the internal processor of the smartphone, a virtual teacher animation procedure is implemented, which demonstrates the correct technique and sets the required pace of the load. The emotional load management module is based on the Stroop effect and boils down to doing mental work under time pressure. The experiments confirmed that the cognitive graphic image makes it possible almost instantly to identify physiological indicators that demonstrate an inadequate response of the body to the load and rest after it.

Conclusions. The developed technology for assessing the adaptive capabilities of the human body under conditions of increased physical and emotional stress provides reliable testing in the field and at home, and the test results can be interpreted by a person without special medical education.

Keywords: information technology on a smartphone, regulatory patterns, body tolerance to physical and emotional stress.

Download full text!

REFERENCES

1. Lazurenko S. I., Biloshitskyi S. V., Semenov A. M. Adaptation and adaptive capabilities of man. Actual problems of education and upbringing of people with special needs. Collection of scientific works. 2013, No. 11(13). P.194-207. http://ap.uu.edu.ua/article/32 (In Ukrainian).

2. Korkushko O. V., Pisaruk A. V., Shatilo V. G., Lishnevskaya V. Yu., Chebotarev N. D., Analysis of heart rate variability in clinical practiceю. Age aspects. K: Institute of Gerontology of the Academy of Medical Sciences, 2002. 189 p. (In Russian).

3. Corr P.B., Yamada K.A.,Witkowski F.V. Mechanisms controlling cardiac autonomic function and their relation to arihythmogenesis. The Heart and Cardiovascular System. 1986. N-Y: Raven Press. 1343-1403.

4. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart Rate Variability. Standards of Measurement, Physiological Interpretation and Clinical Use. Circulation. 1996. Vol. 93. P. 1043-1065.

5. Prokopiev N.Ya., Kolunin E.T., Gurtovaya M.N., Mitasov D.I. Physiological approaches to the evaluation of functional stress tests. Basic research. 2014. No. 2. P. 146-150. (In Russian).

6. Sidorov S.P., Perkhurov A.M., Stefan O.S. The significance of the correct implementation of the functional test methodology with 20 squats in assessing the state of the cardiovascular system of young athletes. Physical education in prevention, treatment and rehabilitation. 2009. No. 2 (29). pp. 39-44. (In Russian).

7. Minina E.N., Fainzilberg L.S., Orikhovskaya K.B. Qualitative assessment of the adaptive reserves of the cardiovascular system based on the regulatory patterns of the reference cycle of a single-channel ECG // Journal “Modern Science. Topical issues of theory and practice. Series natural and technical sciences. – 2016. – No. 8. P. 103-113. (In Russian).

8. Baevsky R.M., Ivanov G.G., Chireikin L.V. Analysis of heart rate variability using various electrocardiographic systems (guidelines). Bulletin of arrhythmology. 2001. No. 24. S. 65-87. (In Russian).

9. Alian A.A., Shelley K.H. Photoplethysmography. Best Practice & Research. Clinical Anaesthesiology. 2014. Vol. 28, No. 4. P. 395-406.
https://doi.org/10.1016/j.bpa.2014.08.006

10. Papon M.T.I., Ahmad I., Saquib N., Rahman A. Non-invasive heart rate measuring smartphone applications using on-board cameras: A short survey. Proceeding of 2015 International Conference on Networking Systems and Security. Dhaka, 2015. P. 1-6.
https://doi.org/10.1109/NSysS.2015.7043533

11. Laure D., I. Paramonov I. Improved Algorithm for Heart Rate Measurement Using Mobile Phone Camera. Proceedings of the 13th Conference of Open Innovations Association FRUCT and 2nd Seminar on e-Tourism for Karelia and Oulu Region. 2013. P. 8593.
https://doi.org/10.23919/FRUCT.2013.8124232

12. Boland P. The emerging role of cell phone technology in ambulatory care. Journal of Ambulatory Care Managemen. 2007. Vol. 30. No. 2. P. 126-133.
https://doi.org/10.1097/01.JAC.0000264602.19629.84

13. Jonathan E., Leahy M. Investigating a smartphone imaging unit for photoplethysmography. Physiol Measurements. 2010. Vol. 31. No. 11. P. 79-83.
https://doi.org/10.1088/0967-3334/31/11/N01

14. Rong-Chao Peng et al. Investigation of Five Algorithms for Selection of the Optimal Region of Interest in Smartphone Photoplethysmography. Journal of Sensors. Volume 2016. Article ID 6830152.
https://doi.org/10.1155/2016/6830152

15. Trofimov P.A., Purtov K.S., Kublanov V.S. Measuring human heart rate variability using a smartphone camera. Computer Image Analysis: Intelligent Solutions in Industrial Networks (CAI-2016): Collection of scientific papers based on the materials of the International Conference May 5-6, 2016. Ekaterinburg: UMC UPI, 2016. P. 134-137.

16. Zenkin A.A. Cognitive computer graphics. M.: Nauka, 1991. 192 p. (In Russian).

17. Pospelov D.A. Cognitive graphics are a window to a new world. Software products and systems. 1992. No. 2. P. 4-6. (In Russian).

18. Fainzilberg L., Potapova T. Computer Analysis and Recognition of Cognitive Phase Spase Electro-Cardio Graphic Image // Proc. of the 6th Int. Conf. on Computer Analysis of Images and Patterns (CAIPS’95). Prague (Czech Republic). 1995. P. 668-673.
https://doi.org/10.1007/3-540-60268-2_362

19. Fainzilberg L.S., Orikhovskaya K.B. Information technology for assessing the adaptive reserves of the body in the field. Cybernetics and computer technology. 2015. Issue. 181. S. 4-22.
https://doi.org/10.15407/kvt181.01.005

20. Fainzilberg L.S. A method of assessing the adequacy of the body’s response to stress. Patent of Ukraine for the invention No. 116548. Bull. No. 27, 2018. (In Ukrainian).

21. Fainzilberg L.S. The method of obtaining a dynamic series of cardio intervals based on the pulse wave. Patent of Ukraine for the invention No. 126520. Bull. No. 43, 2022. (In Ukrainian).

22. Fainzilberg L.S. Intelligent digital medicine tools for home use. Clinical informatics and telemedicine. 2020. Vol. 15. Issue. 16. S. 45-56. (In Russian).
https://doi.org/10.31071/kit2020.16.03

23. Lupanov VP, Nuraliev EYu, Sergienko IV. Funkcionalnye nagruzochnye proby v diagnostike ishemicheskoj bolezni serdcza, ocenke riska oslozhnenij i prognoza. 2016. M.: Izd-vo OOO «PatiSS». (In Russian)

24. Aronov D.M., Lupanov V.P. Functional tests in cardiology. M.: Medpress-inform, 2002. 296 p. (In Russian)

25. Halson S.L., Jeukendrup A.E. Does Overtraining Exist?An Analysis of Overreaching and Overtraining Research. Sports Med. 2004. Vol. 34, No. 14. P. 967-981.
https://doi.org/10.2165/00007256-200434140-00003

26. Prokopiev N.Ya., Kolunin E.T., Gurtovaya M.N. et al. Physiological approaches to the assessment of functional stress tests. Basic research. 2014. No. 2. P. 146-150. (In Russian)

27. Sidorov S.P., Perkhurov A.M., Stefan O.S. The value of the correct implementation of the functional test technique with 20 squats in assessing the state of the cardiovascular system of young athletes. Physical education in prevention, treatment and rehabilitation. 2009. No. 2. P. 39-44. (In Russian)

28. Trigranyan R.A. Stress and its importance for the body. M.: Nauka, 1988. 176 p. (In Russian)

29. Kornatsky V.M. Tretyak I.V. Influx of psychoemotional disorders on the development and overcoming of cardiovascular pathology. Ukrainian Cardiology Journal “Ukrcardio”.2008. No. 6. P. 94-100. (In Russian)

30. Fainzilberg L.S., Kondratyuk T.V., Semergey N.A. ANTISTRESS is a new information technology for managing the regulatory systems of the human body based on biofeedback. Control systems and machines. 2011. No. 3. P. 62-72. (In Russian)

31. Williams, J.M.G., Mathews, A., MacLeod, C. The emotional Stroop task and psychopathology. Psychol. Bull. 1996. No. 120. P. 3-24.
https://doi.org/10.1037/0033-2909.120.1.3

32. Esgalhado G, Pereira H., Silva P.Adaptation of an Emotional Stroop Test for Screening of Suicidal Ideation in Portugal. Behav. Sci. 2022, No. 12, P. 281-292.
https://doi.org/10.3390/bs12080281

33. Lamers M.J.M., Roelofs A., Rabeling-Keus I.M. Selective attention and response set in the Stroop task. Memory & Cognition 2010, No. 38, P. 893-904.
https://doi.org/10.3758/MC.38.7.893

34. Gritsenko V.I., Fainzilberg L.S., Kravchenko A.N., Korchinskaya Z.A., Orikhovskaya K.B., Pasko V.S., Stanislavskaya S.S. Cognitive graphic images in the task of evaluating the body’s response to stress by the phasegraphy method. Control systems and machines. 2016. No. 6, pp. 24-33. http://dspace.nbuv.gov.ua/handle/123456789/117310. (In Russian).
https://doi.org/10.15407/usim.2016.06.024

Received 16.09.2022