Assessing the human condition in medical cyber physical system based on microservice architecture
| dc.citation.conference | Volume 6, № 2 | |
| dc.citation.epage | 120 | |
| dc.citation.journalTitle | Advances in Cyber-Physical Systems | |
| dc.citation.spage | 112 | |
| dc.contributor.affiliation | Lviv Polytechnic National University | |
| dc.contributor.affiliation | Technical University of Munich | |
| dc.contributor.author | Havano, Bohdan | |
| dc.contributor.author | Morozov , Mykola | |
| dc.date.accessioned | 2022-12-01T09:24:21Z | |
| dc.date.available | 2022-12-01T09:24:21Z | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2022 | |
| dc.description.abstract | The goal of the work is to propose architectural and information model for assessing the human condition on the basis of microservice architecture in medical cyberphysical system, which, in contrast to the known models for assessing the human condition, can simultaneously provide scaling, fault tolerance and increase the speed of human condition assessment. The theoretical substantiation and the new decision of an actual scientific problem of development and research means of an estimation of a human condition in medical cyber-physical system have been considered. These means involve the parallel processing of data on vital signs of the human condition, organizing the means of information processing into separate independent logical elements – microservices, in comparison with other existing medical cyber-physical systems. An architectural model based on microservice architecture has been proposed. | |
| dc.format.pages | 112-120 | |
| dc.identifier.citation | Havano B. Assessing the human condition in medical cyber physical system based on microservice architecture / Bohdan Havano, Mykola Morozov // Advances in Cyber-Physical Systems. – Lviv : Lviv Politechnic Publishing House, 2021. – Volume 6, № 2. – P. 112–120 . – Bibliography: 14 titles. | |
| dc.identifier.doi | https://doi.org/10.23939/acps2021.02.112 | |
| dc.identifier.uri | https://ena.lpnu.ua/handle/ntb/57241 | |
| dc.language.iso | en | |
| dc.publisher | Lviv Politechnic Publishing House | |
| dc.relation.ispartof | Advances in Cyber-Physical Systems | |
| dc.relation.references | [1] Melnyk, A. et al. (2020) “Investigation of wireless pulse oximeters for smartphone-based remote monitoring of Lung Health”, Advances in Cyber-Physical Systems, 5(2), pp. 70–76. doi: 10.23939/acps2020.02.070. [2] Melnyk, A. et al. (2021) “HealthSupervisor: Mobile Application for Round-the-Clock Remote Monitoring of the Human Func tional State”, CEUR-WS, 2853, pp. 24–37. Available at: http://ceur-ws.org/Vol-2853/keynote3.pdf (Accessed: 9 October 2021). [3] Mendez, E. O. and Ren, S. (2012) “Design of cyber-physical interface for Automated Vital Signs Reading in electronic medical records systems”, 2012 IEEE International Conference on Electro/Information Technology, pp. 1–10. doi: 10.1109/eit.2012.6220696. [4] Gravina, R. et al. (2017) “Cloud-based activity-AASERVICE cyber–physical framework for human activity monitoring in mobility”, Future Generation Computer Systems, 75, pp. 158-171. doi: 10.1016/j.future.2016.09.006. [5] Zhang, Y. et al. (2017) “Health-CPS: Healthcare Cyber-Physical System assisted by Cloud and Big Data”, IEEE Systems Journal, 11(1), pp. 88–95. doi: 10.1109/jsyst.2015.2460747. [6] Bazzani, M. et al. (2012) “Enabling the IOT paradigm in E-health solutions through the virtus middleware”, 2012 IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications, pp. 1954–1959. doi: 10.1109/trustcom.2012.144. [7] Corredor, I. et al. (2014) “A lightweight web of things open platform to facilitate context data management and personalized healthcare services creation”, International Journal of Environmental Research and Public Health, 11(5), pp. 4676– 4713. doi: 10.3390/ijerph110504676. [8] Páez, D. G. et al. (2014) “Big Data and IOT for chronic patients monitoring”, Ubiquitous Computing and Ambient Intelligence. Personalisation and User Adapted Services, 8867, pp. 416–423. doi: 10.1007/978-3-319-13102-3_68. [9] Maia, P. et al. (2014) “A web platform for interconnecting body sensors and improving health care”, Procedia Computer Science, 40, pp. 135–142. doi: 10.1016/j.procs.2014.10.041. [10] Sebestyen, G. et al. (2014) “EHealth solutions in the context of internet of things”, 2014 IEEE International Conference on Automation, Quality and Testing, Robotics, pp. 1–6. doi: 10.1109/aqtr.2014.6857876. [11] Suciu, G. et al. (2015) “Big Data, internet of things and cloud convergence – an architecture for secure E-Health Applications”, Journal of Medical Systems, 39(11). doi: 10.1007/s10916-015- 0327-y. [12] Rathore, M. M. et al. (2016) “Real-time medical emergency response system: Exploiting IOT and Big Data for Public Health”, Journal of Medical Systems, 40(12). doi: 10.1007/s10916-016- 0647-6. [13] Caporuscio, M. and Ghezzi, C. (2015) “Engineering future internet applications: The prime approach”, Journal of Systems and Software, 106, pp. 9–27. doi: 10.1016/j.jss.2015.03.102. [14] Kopczyk, D. (2018) Quantum Machine Learning for Data scientists, arXiv.org. Available at: https://arxiv.org/abs/ 1804.10068 (Accessed: 9 October 2021). | |
| dc.subject | medical cyber-physical system, microservices, assessing the human condition, indicators, asynchronous data processing | |
| dc.title | Assessing the human condition in medical cyber physical system based on microservice architecture | |
| dc.type | Article |
Files
Original bundle
1 - 1 of 1