Stabilization and recovery assistant of people with disabilities based on artificial intelligence methods
- Authors: Kiselev G.A.1,2, Blagosklonov N.A.2, Nikolaev A.A.2
-
Affiliations:
- RUDN University
- Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences
- Issue: Vol 32, No 3 (2024)
- Pages: 283-293
- Section: Computer Science
- URL: https://journals.rcsi.science/2658-4670/article/view/315400
- DOI: https://doi.org/10.22363/2658-4670-2024-32-3-283-293
- EDN: https://elibrary.ru/EUNYIE
- ID: 315400
Cite item
Full Text
Abstract
Chronic non-communicable diseases account for more than 70% of global mortality statistics. The main share is made up of diseases of the cardiovascular system. Adequate preventive measures-impact on controllable and conditionally controllable risk factors-can reduce the contribution of these diseases to the structure of mortality. A significant effect can be achieved with an adequately selected level of physical activity, but doctors do not always recommend specific actions to patients. This article describes a prototype of a cognitive assistant for constructing personalized plans for therapeutic physical exercises for relatively healthy people and people suffering from cardiovascular diseases. The developed system consists of two main components: a cardiovascular risk assessment module and an exercise planning module. The risk assessment module consists of a knowledge base and an argumentative reasoning algorithm. Its task is to identify risk factors and levels, which is dual in nature: in the case of monitoring a relatively healthy user, the risk of developing cardiovascular disease is assessed, while in the case of interaction of the system with a user with cardiovascular disease, the risk of complications of a chronic form is assessed-development of a cardiovascular event. The exercise planning module includes an exercise database and a scheduler algorithm. The planning algorithm selects optimal therapeutic physical exercises according to optimal criteria, in order to form a plan that will not harm the patient and will increase his physical performance. The developed mechanism allows you to create training scenarios for users with any level of initial training, taking into account the available sports equipment, the preferred location for training (home, street, gym) and at any level of the cardiovascular continuum.
About the authors
Gleb A. Kiselev
RUDN University; Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences
Email: kiselev@isa.ru
ORCID iD: 0000-0001-9231-8662
Scopus Author ID: 57195683637
ResearcherId: Y-6971-2018
Candidate of Technical Sciences, Senior Lecturer at the Department of Mathematical Modeling and Artificial Intelligence of RUDN University; Researcher of Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences
6 Miklukho-Maklaya St, Moscow, 117198, Russian Federation; 44 Vavilova St, bldg 2, Moscow, 119333, Russian FederationNikolay A. Blagosklonov
Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences
Email: nblagosklonov@frccsc.ru
ORCID iD: 0000-0002-5293-8469
Scopus Author ID: 57206274545
ResearcherId: ABG-2002-2021
Researcher
44 Vavilova St, bldg 2, Moscow, 119333, Russian FederationArtem A. Nikolaev
Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences
Author for correspondence.
Email: nicepeopleproject@gmail.com
ORCID iD: 0000-0003-4561-8990
ResearcherId: G-9622-2018
Senior developer
44 Vavilova St, bldg 2, Moscow, 119333, Russian FederationReferences
- Top 10 leading causes of death in the world https://www.who.int/ru/news-room/fact-sheets/detail/the-top-10-causes-of-death/. 2020.
- WHO publishes statistics on the leading causes of death and disability worldwide for the period 2000-2019 https://www.who.int/ru/news/item/09122020horevealsleadingcausesof-death-and-disability-worldwide-2000-2019/. 2019.
- Balanova, Y. Arterial hypertension in the Russian population: prevalence, contribution to survival and mortality, possibilities for reducing socio-economic damage (Abstract for the scientific degree of Doctor of Medical Sciences, 2021).
- Kontsevaya, A., Drapkina, O. & Balanova, Y. Economic damage from cardiovascular diseases in the Russian Federation in 2016. Rational pharmacotherapy in cardiology 14, 156-166 (2018).
- Boytsov, S., Chuchalin, A. & Arutyunov, G. Prevention of chronic non-infectious diseases: Recommendations. Profmedforum (2013).
- Cardiovascular prevention 2017. Russian national recommendations 122 pp. (2018).
- P4-medicine a new direction in the development of healthcare https://www.dirklinik.ru/article/5004p-meditsina-novoe-napravlenie-razvitiya-zdravoohraneniya/. 2023.
- Suchkov, S., H., A. & Antonova, E. Personalized medicine as an updated model of the national healthcare system.Part 1. Strategic aspects of infrastructure. Russian Bulletin of Perinatology and Pediatrics 62, 7-14 (2017).
- Savilov, E. & Shugaeva, S. Risk factor: theory and practice of application in epidemiological studies. Epidemiology and infectious diseases 22, 306-310 (2017).
- World Health Organization. News bulletin. Physical activity. https://www.who.int/ru/newsroom/fact-sheets/detail/physical-activity/. 2023.
- Shebeko, L., Vlasova, S., Germanovich, L. & Belyakovskaya, N. Physical rehabilitation of patients with arterial hypertension. Bulletin of the Transbaikal State University 93, 80-87 (2013).
- Bubnova, M. & Aronov, D. Methodic recommendations. Maintaining physical activity of those with limitations in health. In Russ. CardioSomatics 7 (ed Boytsov, S.) 5-50 (2016).
- Trenkwalder, P. Preventing thecardiovascular complications of hypertension. European Heart Journal Supplements 6, H37-H42 (2004).
- ESC recommendations for the prevention of cardiovascular diseases in clinical practice. Russian Journal of Cardiology. Clinical recommendations. Arterial hypertension in adults 27, 191-288 (2022).
- Tolpygina, S. & Martsevich, S. Cardiac risk stratification in stable coronary artery disease. In Russ. The Clinician 14, 24-33. doi: 10.17650/1818-8338-2020-14-1-2-24-33 (2020).
- Kobrinsky, B., Kadykov, A., Poltavskaya, M., Blagoslonov, N. & Kovelkova, M. Principles of functioning of an intelligent system for dynamic control of risk factors and the formation of recommendations for health care. Preventive Medicine 22, 78-84 (2019).
- Osipov, G. Acquisition of knowledge by intelligent systems: Fundamentals of theory and technology Russian (Fizmatlit, 1998).
- Drapkina, O., Novikova, N. & Dzhioyeva, O. Methodological recommendations: ”Current opportunities and prospects of complex physical activity of patients with cardiovascular pathology”. In Russ. Russian Journal of Preventive Medicine 23, 61-119. doi: 10.17116/profmed20202303261 (2020).
- Dibben, G., Faulkner, J., Oldridge, N., Rees, K., Thompson, D., Zwisler, A.-D. & Taylor, R. Exercisebased cardiac rehabilitation for coronary heart disease. Cochrane Database of Systematic Reviews 11. doi: 10.1002/14651858.CD001800.pub4 (2021).
- Lyamina, N., Karpova, E., Kotelnikova, E. & Bizyaeva, E. Physical training in the rehabilitation and prevention in patients with ischemic heart disease after percutaneous coronary interventions: the borders of efficiency and safety. In Russ. Russian Journal of Cardiology, 93-98. doi: 10.15829/1560-4071-2014-6-93-98 (2014).
Supplementary files
