Mobile multiparameter hardware and software complex for monitoring human health indicators

The purpose of the research is to develop the concept of a software and hardware complex for monitoring the func- tional state of a person. The complex being created should be multi-purpose and universal  in  terms of  the age of patients and the applicability of the complex in various scenarios, including for personal use by patients, in rehabilitation, for operational monitoring of the condition of athletes, pilots, drivers and other categories, including those working in extreme conditions. 
Methods. A comparative analysis of noninvasive methods and technical means of obtaining information about significant parameters of the functional state of the human body is presented. The results of the analysis are summarized in order to form requirements for hardware and software tools for monitoring the functional state of a person. A mathematical model is analyzed allowed to obtain an integral estimation of the functional state of a person. 
Results. Significant parameters and characteristics of the human body amenable to objective instrumental control have been  identified. These parameters are necessary to create a software and hardware complex  that allows real-time monitoring of the functional state of a person. The requirements for the nodes of the complex are defined. It makes possible to assess the functional state both with and without distraction of the object of control from professional activity. The composition and characteristics of measurement channels are formulated. A method of forming an assessment of a person's functional state based on the use of artificial intelligence methods is proposed. 
Conclusion. The proposed hardware and software package satisfies  the set goals and objectives. The completed research allows us  to  recommend  the complex being developed  for use by medical personnel  in order  to support medical decision-making. The complex under development  is multi-purpose and can be useful  for personal use by patients, including in home telemedicine, as well as athletes who need to continuously monitor the body's state during the training process. The complex can be used by people whose professional activity is associated with risks in the event of a decrease in the functional parameters of the body. 

1. Nguyen M.T., Yuldashev Z.M. Method and hardware and software package for a comprehensive assessment of an athlete’s physiological reserves during training. Biotechnosphere = Biotekhnosfera. 2020;(5):3–11. (In Russ.)

2. Baranov V.A., Pecherskaya E.A., Safronov M.I., Timokhina O.A. Information and measurement system for telemedicine monitoring of the patient’s condition COVID-19. Izmerenie. Monitoring. Upravlenie. Kontrol' = Measurement. Monitoring. Management. Control. 2021;1(35):85–92. (In Russ.)

3. Glushchenko V.A., Irklienko E.K. Cardiovascular morbidity is one of the most important health problems. Meditsina i organizatsiya zdravookhraneniya = Medicine and Healthcare Organization. 2019;(1):56–63. (In Russ.)

4. Samorodskaya I.V., Starinskaya M.A., Boytsov S.A. Dynamics of regional mortality rates from cardiovascular diseases and cognitive impairments in Russia 2019–2021. Rossiiskii kardiologicheskii zhurnal = Russian Journal of Cardiology. 2023;(28):94–101. (In Russ.) https://doi.org/10.15829/1560-4071-2023-5256

5. Frolov A.V., Melnikova O.P., Vorobyov A.P., Vaikhanskaya T.G. Digital electrocardiographic complex for risk stratification of atrial fibrillation symptoms. Sovremennye tekhnologii v meditsine = Modern Technologies in Medicine. 2024;16(3):43–50. (In Russ.) https://doi.org/10.17691/stm2024.16.3.05

6. Khairullin A.A., Ostanina M.V., Poghosyan A.M. Possibilities of pulse oximetry in the diagnosis of chronic arterial insufficiency of the lower extremities. Smolenskii meditsinskii al'manakh = Smolenskiy Medical Almanac. 2015;(1):146–147. (In Russ.)

7. Antonov A.A., Burov N.E. System hardware monitoring (physiological aspects). Vestnik Intensivnoi terapii = Bulletin of Intensive Care. 2010;(3):8–12. (In Russ.)

8. Borisenko T.L., Snezhitsky V.A. The clinical significance of nonlinear parameters of heart rate variability in patients with cardiovascular diseases. Zhurnal Grodnenskogo gosudarstvennogo meditsinskogo universiteta = Journal of the Grodno State Medical University. 2020;18(3):223–229. (In Russ.) https://doi.org/10.25298/2221-8785-2020-18-3-223-229

9. Uspensky V.M. Informational function of the heart. Theory and practice of diagnostics of diseases of internal organs by the method of information analysis of electrocardiosignals. Moscow: Tsentr noosfernogo zdorov’ya; 2023. 272 p. (In Russ.)

10. Khadartsev A.A., Eskov V.M., Kozyrev K.M., Gontarev S.N. Medical and biological theory and practice. Belgorod: Belgorodskaya oblastnaya tipografiya; 2011. 231 p. (In Russ.)

11. Yuldashev Z., Nemirko A., Manilo L., Mikhaylov E., Lebedev D., Anisimov A. Processing of Synchronous Recordings of Surface ECG and Intracardiac Potentials for Diagnostics of Dangerous Heart Rate Disturbances. Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT). Yekaterinburg, 25–26 April 2019.

12. Furman Ya.A., Sevastyanov V.V., Stulin I.D., Ivanov K.O. Amplitude-frequency mapping to support a clinician in the visual analysis of an electroencephalogram. Vestnik Povolzhskogo gosudarstvennogo tekhnologicheskogo universiteta. Seriya: Radiotekhnich- eskie i infokommunikatsionnye sistemy = Bulletin of the Volga State Technological University. Series: Radio Engineering and Infocommunication Systems. 2018;(3):20–38. https://doi.org/10.15350/2306-2819.2018.3.20

13. Belyaev O.V., Samygin D.V. Recommendations of the Expert Council on Neurophysiology of the Russian Antiepileptic League for routine EEG. Epilepsiya i paroksizmal'nye sostoyaniya = Epilepsy and Paroxysmal States. 2016;8(4):99–108.

14. Zakharov S.M., Znayko G.G. Spectral analysis of electrocardiosignals. Voprosy radioelektroniki = Radio Electronics Issues. 2017;(3):110–115. (In Russ.)

15. Park J., Seok H.S., Kim S.-S., Shin H. Photoplethysmogram Analysis and Applications: An Integrative Review. Front. Physiol = Front. Physiol. 2022;(12):808451. https://doi.org/10.3389/fphys.2021.808451

16. Kharlanova K.S., Selikhov A.V., Revyakina M.O. A channel for assessing the state of the human cardiovascular system based on multiparametric signal monitoring with joint signal processing. In: Nauka molodykh – budushchee Rossii: sbornik nauchnykh statei IX Mezhdunarodnoi nauchnoi konferentsii perspektivnykh razrabotok molodykh uchenykh (12–13 dekabrya 2024 goda) = Science of the young – the future of Russia: Collection of scientific articles of the IX International Scientific Conference of promising developments of Young Scientists, 12–13 December 2024. Vol. 3. Kursk: Universitetskaya kniga; 2024. P. 219–227. (In Russ.)

17. Dembovsky M.V., Pisareva A.V. Development of a biotechnical magnetoplethysmography system for monitoring respiratory rate and heart rate. Sistemnyi analiz i upravlenie v biomeditsinskikh sistemakh = System Analysis and Management in Biomedical Systems. 2020;19(4):119–126.

18. Yurchenko H.Yu., Neighbors A.I. Assessment of prospects for the development of mobile medicine. Innovatsii i investitsii = Innovations and Investments. 2019;(5):298–304. (In Russ.)

19. Zhivolupova Yu.A. Information and methodological support for a remote cardiorespiratory monitoring system for the diagnosis of sleep-breathing disorders. Biotekhnosfera = Biotechnosphere. 2019;(6):41–46. (In Russ.)

20. Novikova E.I., Andrianova E.A., Udodova E.E., et al. Development of an expert system for the diagnosis of lung diseases based on neural network modeling. Sistemnyi analiz i upravlenie v biomeditsinskikh sistemakh = System Analysis and Management in Biomedical Systems. 2021;20(1):155–159. (In Russ.)