{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T00:47:23Z","timestamp":1760230043292,"version":"build-2065373602"},"reference-count":60,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,7,6]],"date-time":"2022-07-06T00:00:00Z","timestamp":1657065600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>The integrated collection of personal health data represents a relevant research topic, which is enhanced further by the development of next-generation mobile networks that can be used in order to transport the acquired medical data. The gathering of personal health data has become recently feasible using relevant wearable personal devices. Nevertheless, these devices do not possess sufficient computational power, and do not offer proper local data storage capabilities. This paper presents an integrated personal health metrics data management system, which considers a virtualized symmetric 5G data transportation system. The personal health data are acquired using a client application component, which is normally deployed on the user\u2019s mobile device, regardless it is a smartphone, smartwatch, or another kind of personal mobile device. The collected data are securely transported to the cloud data processing components, using a virtualized 5G infrastructure and homomorphically encrypted data packages. The system has been comprehensively assessed through the consideration of a real-world use case, which is presented.<\/jats:p>","DOI":"10.3390\/sym14071387","type":"journal-article","created":{"date-parts":[[2022,7,6]],"date-time":"2022-07-06T21:15:52Z","timestamp":1657142152000},"page":"1387","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Personal Health Metrics Data Management Using Symmetric 5G Data Channels"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6577-1904","authenticated-orcid":false,"given":"Razvan","family":"Bocu","sequence":"first","affiliation":[{"name":"Department of Mathematics and Computer Science, Transilvania University of Brasov, 500036 Bra\u0219ov, Romania"},{"name":"Department of Research and Technology, Siemens Industry Software, 500203 Bra\u0219ov, Romania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7904-6727","authenticated-orcid":false,"given":"Anca","family":"Vasilescu","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Computer Science, Transilvania University of Brasov, 500036 Bra\u0219ov, Romania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6767-5561","authenticated-orcid":false,"given":"Delia Monica","family":"Duca Iliescu","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Computer Science, Transilvania University of Brasov, 500036 Bra\u0219ov, Romania"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,6]]},"reference":[{"key":"ref_1","unstructured":"Gentry, C. 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