from 01.01.2018 to 01.01.2020
Moskva, Moscow, Russian Federation
Physical inactivity is one of the most important risk factors for many chronic diseases in older age. To address this problem, the consequences of which have a significant impact on the sustainability of national wealth in many developed countries, consumer technologies can be used to provide easy-to-use tools to enable older people to optimize their health-related quality of life. and promote active and healthy longevity. This white paper describes a technical platform called vINCI, resulting from the integration of consumer technology with assisted living solutions and services, where multiple wearable devices work together to create an aggregated solution capable of capturing various aspects of events leading to a reduction in perceived quality. a health-related life that is commonly associated with old age. Based on the results of specialized medical examinations, vINCI technology allows older people not only to self-assess their level of physical activity, but also to change their behavior and lifestyle in the long term.
consumer technology integration, assisted lifestyle, quality of life, platform
1. Ivanova S.P. Problemy deinstitucializacii tradicionnyh atributov i gendernyh stereotipov / A.I. Myasoedov, S.P. Ivanova // Problemy sovremennogo pedagogicheskogo obrazovaniya. 2020. № 66-2. 313-316
2. Myasoedov A.I. Donorskoe povedenie "tret'ego sektora": pod upravleniem sostradaniya / A.I. Myasoedov // Nauchnyy rezul'tat. Social'nye i gumanitarnye issledovaniya. 2020. T. 6. № 2. S. 50-62. DOI:https://doi.org/10.18413/2408-932X-2020-6-2-0-5
3. Myasoedov A.I. Intellektual'nyy kapital v svete kreativnosti i konkurentosposobnosti: obzor nematerial'nyh aktivov organizaciy na primere Ukrainy / A.I. Myasoedov // Nauchnye issledovaniya i razrabotki. Social'no-gumanitarnye issledovaniya i tehnologii. 2020. T. 9. № 2. S. 57-68.
4. Myasoedov A.I. Korporativnoe volonterstvo v social'noy missii krupnyh predpriyatiy / A.I. Myasoedov // Nauchnyy rezul'tat. Social'nye i gumanitarnye issledovaniya. 2021. T. 7 № 1. S. 44-55. DOI:https://doi.org/10.18413/2408-932X-2021-7-1-0-4
5. Myasoedov A.I. Model' effektivnosti dlya ocenki intellektual'nogo kapitala / A.I. Myasoedov // Nauchnye issledovaniya i razrabotki. Social'no-gumanitarnye issledovaniya i tehnologii. 2021. T. 10. № 1. S. 84-91.
6. Radosteva M.V. Social'no-ekonomicheskie potrebnosti kak odna iz bazovyh kategoriy ekonomiki / M.V. Radosteva // Aktual'nye problemy ekonomicheskih issledovaniy. M., 2012. S. 88-99
7. Radosteva M.V. Uroven' i kachestvo zhizni naseleniya: nestandartnyy podhod k issledovaniyu problemy / M.V. Radosteva // Nauchnye trudy Moskovskogo gumanitarnogo universiteta. - 2012. - № 137. - S. 40-45.
8. A. Bowling, “Quality of life in healthcare decisions,” in Medical Ethics and the Elderly, 4th ed., G. Rai, Ed. London: CRC Press, 2014, ch. 16, p. 147.
9. B. Lamboy, C. Leon, and P. Guilbert, “Troubles de´pressifs et recours aux soins dans la population franc¸aise a` partir des donne´es du barome`tre sante´ 2005,” Revue d’e´pide´miologie et de sante´ publique, vol. 55, no. 3, pp. 222-227, 2007.
10. D. Betts et al., Exploring CQRS and Event Sourcing: A journey into high scalability, availability, and maintainability with Windows Azure, ser. Microsoft patterns and practices. Microsoft, 2012, iSBN: 978-1- 62114-016-0.
11. D. Merkel, “Docker: lightweight Linux containers for consistent de- velopment and deployment,” Linux Journal, vol. 2014, no. 239, p. 2, 2014.
12. E. A. Brewer, “Kubernetes and the path to cloud native,” in Proceedings of the Sixth ACM Symposium on Cloud Computing. Kohala Coast, Hawaii: ACM, 2015, pp. 167-167.
13. Gartner, “IoT adoption is driving the use of platform as a service - press release,” 2016. [Online]. Available: https://www.gartner.com/newsroom/ id/3241817
14. J. M. Batalla, M. Gajewski, W. Latoszek, P. Krawiec, C. X. Mavromous- takis, and G. Mastorakis, “ID-based service-oriented communications for unified access to IoT,” Computers & Electrical Engineering, vol. 52, pp. 98 - 113, 2016.
15. L. Montanini, A. Del Campo, D. Perla, S. Spinsante, and E. Gambi, “A footwear-based methodology for fall detection,” IEEE Sensors Journal, vol. 18, no. 3, pp. 1233-1242, 2018.
16. M. Mettler, “Blockchain technology in healthcare: The revolution starts here,” in 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom), Sep. 2016, pp. 1-3.
17. S. Spinsante and L. Scalise, “Measurement of elderly daily physical activity by unobtrusive instrumented shoes,” in MeMeA 2018 - 2018 IEEE International Symposium on Medical Measurements and Applications, Proceedings, 2018.
18. S. Spinsante, M. Fagiani, M. Severini, S. Squartini, F. Ellmenreich, and G. Martelli, “Depth-based fall detection: Outcomes from a real life pilot,”Lecture Notes in Electrical Engineering, vol. 544, pp. 287-299, 2018.
19. S. Spinsante, M. Ricciuti, E. Cippitelli, and E. Gambi, “Fall detection with kinect in top view: Preliminary features analysis and characterization,” Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 233, pp. 153-162, 2018.
20. U. Hunkeler, H. L. Truong, A. Stanford-Clark et al., “MQTT-S: A pub- lish/subscribe protocol for wireless sensor networks,” in Communication systems software and middleware and workshops, 2008. 3rd conf. on. IEEE, 2008, pp. 791-798.
21. vINCI Project Consortium, “clinically-validated integrated support for assistive care and lifestyle improvement: the human link,” 2018.
22. X. Meng, J. Bradley, B. Yavuz et al., “Mllib: Machine learning in apache spark,” The Journal of Machine Learning Research, vol. 17, no. 1, pp. 1235-1241, 2016.