Architecture of the Software Suite for the Design of Medical Instrument-computer Systems for Real-Time Monitoring
( Pp. 278-295)
More about authors
Dvoretsky Artur G.
postgraduate student, Department of Industrial Programming, Institute for Advanced Technologies and Industrial Programming
MIREA – Russian Technological University
Moscow, Russian Federation Barabanova Elizaveta A. Dr. Sci. (Eng.), Associate Professor; Head, Laboratory of Infrastructure Systems
Institute of Management Problems named after V.A. Trapeznikov of the Russian Academy of Sciences
Moscow, Russian Federation
MIREA – Russian Technological University
Moscow, Russian Federation Barabanova Elizaveta A. Dr. Sci. (Eng.), Associate Professor; Head, Laboratory of Infrastructure Systems
Institute of Management Problems named after V.A. Trapeznikov of the Russian Academy of Sciences
Moscow, Russian Federation
Abstract:
This paper proposes an information system architecture to support the design of medical instrument-computer systems for real-time monitoring. The proposed architecture allows the selection of one of three types of simulation for the operation of a medical instrument-computer system, depending on the buffer size of its processing unit, and also enables the analysis of the non-stationary performance characteristics of such systems. An ER diagram of the database has been developed to ensure the storage and reuse of calculation results. To formalise the operational processes of medical instrument-computer systems, IDEF0 structural-functional models have been constructed for the AS-IS and TO-BE states, which enable the identification of the design evaluation loop. The mathematical basis for calculating the system’s performance characteristics is provided by the theory of queuing systems. The paper analyses the FLOPs complexity of algorithms for analytical, numerical and simulation modelling of a queuing system with a limited buffer and impatient requests. The results obtained demonstrate the advisability of taking into account the computational complexity of algorithms when selecting a method for modelling system operation.
How to Cite:
Dvoretsky A.G. and Barabanova E.A. Architecture of the software suite for the design of medical instrument-computer systems for real-time monitoring. Computational Nanotechnology. 13, 2 (2026), 278–295. DOI: 10.33693/2313-223X-2026-13-2-278-295. EDN: XMWFMQ
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Luzgina V.S., Shumarov O.E., Shepelev M.I., Nikulin V.V. Connecting medical equipment to a virtual local area network VLAN. Ogarev-Online. 2023. No. 15 (200). (In Rus.)
Novikov M.K., Korovina E.N., Novikova E.I., Sergeeva M.A. Design of a medical information subsystem for dispensary observation. Systems Analysis and Control in Biomedical Systems. 2024. Vol. 23. No. 1. Pp. 120–125. (In Rus.)
Pervukhin D.V., Isaev E.A., Rytikov G.O. et al. Comparative analysis of theoretical models of cascade, iterative and hybrid approaches to IT project life cycle management. Business Informatics. 2020. Vol. 14. No. 1. Pp. 32–40. (In Rus.). DOI: 10.17323/2587-814X.2020.1.32.40.
Pugachev P.S., Gusev A.V., Kobyakova O.S. et al. Global trends in the digital transformation of the healthcare industry. National Health. 2021. No. 2 (2): Pp. 5–12. (In Rus.). DOI: 10.47093/2713-069X.2021.2.2.5-12.
Barabanova E.A., Dvoretsky A.G. Transient behaviar of queuing system with correlated arrival flows and impatient customers. In: Proceedings of 9th International Conference on Information, Control, and Communication Technologies (ICCT 2025). Gomel, Belarus: IEEE, 2025. Pp. 1–3.
Doehring D., Christmann L., Schlottke-Lakemper M. et al. Fourth-order paired-explicit Runge–Kutta methods. Computational Science and Engineering. 2025. DOI: 10.1007/s44207-025-00005-4.
Khiar Y., Mainar E., Royo-Amondarain E. Factorizations and accurate computations with min and max matrices. Symmetry. 2025. Vol. 17. No. 5. Art. 684. DOI: 10.3390/sym17050684.
Pogue T.E., Nicolici N. Karatsuba matrix multiplication and its efficient custom hardware implementations. IEEE Transactions on Computers. 2025. Vol. 74. No. 4. Pp. 1377–1391. DOI: 10.1109/TC.2025.3525606.
Swailem M., Dobramysl U., Mukhamadiarov R.I., Täuber U.C. Agent-based Monte Carlo simulations for reaction-diffusion models, population dynamics, and epidemic spreading. American Journal of Physics. 2025. Vol. 93. No. 8. Pp. 659–681. DOI: 10.1119/5.0282284.
Venkatesha G., Dinesh S., Manjunath M. et al. Li-Fi technology based patient health monitoring and tracking system. Perspectives in Communication, Embedded-systems and Signal-processing – PiCES 5. 2021. No. 2. Pp. 22–26. https://doi.org/10.5281/zenodo.4902957.
Vishnevsky V., Vytovtov K., Barabanova E.; Semenova O. Transient behavior of the MAP/M/1/N queuing system. Mathematics. 2021. No. 9. P. 2559. (In Rus.). DOI: 10.3390/math9202559.
Zhang J., Cui S. Investigating the number of Monte Carlo simulations for statistically stationary model outputs. Axioms. 2023. Vol. 12. No. 5. Art. 481. DOI: 10.3390/axioms12050481.
Keywords:
medical instrumentation and computer system, information system, architecture, queueing system, simulation modelling, FLOPs complexity.
