DEVELOPMENT OF NEURAL NETWORK ALGORITHMS FOR ASSESSING THE CARDIOVASCULAR SYSTEM STATE OF STUDENTS IN PLANNING PHYSICAL EDUCATION CLASSES
- Authors: Shutova T.N.1, Nosov S.M.2, Shutov I.D.2, Andrushevsky A.T.2
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Affiliations:
- Plekhanov Russian University of Economics
- Russian Economic University after G.V. Plekhanov
- Issue: No 6 (2025)
- Pages: 115-121
- Section: Physical education and professional physical training
- URL: https://ogarev-online.ru/1994-4683/article/view/301491
- DOI: https://doi.org/10.5930/1994-4683-2025-115-121
- ID: 301491
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Abstract
The purpose of the study is to conduct a theoretical analysis of the problem of artificial intelligence (AI) development and to develop an algorithm for accounting for the state of the cardiovascular system in the planning of physical culture and sports activities.
Research methods and organization. The study was conducted in 2025 at the Plekhanov Russian University of Economics (Moscow) as part of a research application to the Russian Science Foundation. A theoretical analysis of the issue was carried out, including a forecast of the development of the international AI market up to 2030.
Research results and conclusions. The developed algorithm is a preliminary stage of the planned scientific research in collaboration with the Russian Science Foundation (RSF). The data collected on the cardiovascular system will be analyzed by AI through an advanced cluster correlation analysis. The program, based on a specific algorithm, will be able to identify and analyze data obtained from various regions of the Russian Federation, in higher educational institutions of different profiles. The algorithm of the program will examine the state of the cardiovascular system comprehensively, creating conditions for data acquisition and exchange for joint scientific research and publications. This will serve as a data processing tool utilizing AI, seeking further recommendations for physical culture and sports engagement, which will facilitate the enhancement of cluster and correlation analysis of the functional state of the cardiovascular system among the student youth, and will establish conditions for data collection, analysis, processing, and exchange, as well as their interpretation.
Research methods and organization. The study was conducted in 2025 at the Plekhanov Russian University of Economics (Moscow) as part of a research application to the Russian Science Foundation. A theoretical analysis of the issue was carried out, including a forecast of the development of the international AI market up to 2030.
Research results and conclusions. The developed algorithm is a preliminary stage of the planned scientific research in collaboration with the Russian Science Foundation (RSF). The data collected on the cardiovascular system will be analyzed by AI through an advanced cluster correlation analysis. The program, based on a specific algorithm, will be able to identify and analyze data obtained from various regions of the Russian Federation, in higher educational institutions of different profiles. The algorithm of the program will examine the state of the cardiovascular system comprehensively, creating conditions for data acquisition and exchange for joint scientific research and publications. This will serve as a data processing tool utilizing AI, seeking further recommendations for physical culture and sports engagement, which will facilitate the enhancement of cluster and correlation analysis of the functional state of the cardiovascular system among the student youth, and will establish conditions for data collection, analysis, processing, and exchange, as well as their interpretation.
About the authors
Tat'yana Nikolaevna Shutova
Plekhanov Russian University of Economics
Email: SHutova.TN@rea.ru
Department of Physical Education, docent, candidate of pedagogical sciences
Sergey Mikhaylovich Nosov
Russian Economic University after G.V. Plekhanov
Ilya Dmitrievich Shutov
Russian Economic University after G.V. Plekhanov
Alexey Tarasovich Andrushevsky
Russian Economic University after G.V. Plekhanov
References
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