{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T15:35:46Z","timestamp":1772292946986,"version":"3.50.1"},"reference-count":64,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2022,11,7]],"date-time":"2022-11-07T00:00:00Z","timestamp":1667779200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"E\u00f6tv\u00f6s Lor\u00e1nd Research Network Secretariat (Development of cyber-medical systems based on AI and hybrid cloud methods)","award":["ELKH K\u00d6-37\/2021"],"award-info":[{"award-number":["ELKH K\u00d6-37\/2021"]}]},{"name":"E\u00f6tv\u00f6s Lor\u00e1nd Research Network Secretariat (Development of cyber-medical systems based on AI and hybrid cloud methods)","award":["2019-1.3.1-KK-2019-00007"],"award-info":[{"award-number":["2019-1.3.1-KK-2019-00007"]}]},{"name":"E\u00f6tv\u00f6s Lor\u00e1nd Research Network Secretariat (Development of cyber-medical systems based on AI and hybrid cloud methods)","award":["TKP2021-NKTA-36"],"award-info":[{"award-number":["TKP2021-NKTA-36"]}]},{"name":"E\u00f6tv\u00f6s Lor\u00e1nd Research Network Secretariat (Development of cyber-medical systems based on AI and hybrid cloud methods)","award":["\u00daNKP-21-3"],"award-info":[{"award-number":["\u00daNKP-21-3"]}]},{"name":"National Research, Development and Innovation Fund of Hungary, financed under the 2019-1.3.1-KK funding scheme","award":["ELKH K\u00d6-37\/2021"],"award-info":[{"award-number":["ELKH K\u00d6-37\/2021"]}]},{"name":"National Research, Development and Innovation Fund of Hungary, financed under the 2019-1.3.1-KK funding scheme","award":["2019-1.3.1-KK-2019-00007"],"award-info":[{"award-number":["2019-1.3.1-KK-2019-00007"]}]},{"name":"National Research, Development and Innovation Fund of Hungary, financed under the 2019-1.3.1-KK funding scheme","award":["TKP2021-NKTA-36"],"award-info":[{"award-number":["TKP2021-NKTA-36"]}]},{"name":"National Research, Development and Innovation Fund of Hungary, financed under the 2019-1.3.1-KK funding scheme","award":["\u00daNKP-21-3"],"award-info":[{"award-number":["\u00daNKP-21-3"]}]},{"name":"National Research, Development, and Innovation Fund of Hungary, financed under the TKP2021-NKTA-36 funding scheme","award":["ELKH K\u00d6-37\/2021"],"award-info":[{"award-number":["ELKH K\u00d6-37\/2021"]}]},{"name":"National Research, Development, and Innovation Fund of Hungary, financed under the TKP2021-NKTA-36 funding scheme","award":["2019-1.3.1-KK-2019-00007"],"award-info":[{"award-number":["2019-1.3.1-KK-2019-00007"]}]},{"name":"National Research, Development, and Innovation Fund of Hungary, financed under the TKP2021-NKTA-36 funding scheme","award":["TKP2021-NKTA-36"],"award-info":[{"award-number":["TKP2021-NKTA-36"]}]},{"name":"National Research, Development, and Innovation Fund of Hungary, financed under the TKP2021-NKTA-36 funding scheme","award":["\u00daNKP-21-3"],"award-info":[{"award-number":["\u00daNKP-21-3"]}]},{"name":"New National Excellence Program of the Ministry for Innovation and Technology","award":["ELKH K\u00d6-37\/2021"],"award-info":[{"award-number":["ELKH K\u00d6-37\/2021"]}]},{"name":"New National Excellence Program of the Ministry for Innovation and Technology","award":["2019-1.3.1-KK-2019-00007"],"award-info":[{"award-number":["2019-1.3.1-KK-2019-00007"]}]},{"name":"New National Excellence Program of the Ministry for Innovation and Technology","award":["TKP2021-NKTA-36"],"award-info":[{"award-number":["TKP2021-NKTA-36"]}]},{"name":"New National Excellence Program of the Ministry for Innovation and Technology","award":["\u00daNKP-21-3"],"award-info":[{"award-number":["\u00daNKP-21-3"]}]},{"name":"Consolidator Researcher program of \u00d3buda University","award":["ELKH K\u00d6-37\/2021"],"award-info":[{"award-number":["ELKH K\u00d6-37\/2021"]}]},{"name":"Consolidator Researcher program of \u00d3buda University","award":["2019-1.3.1-KK-2019-00007"],"award-info":[{"award-number":["2019-1.3.1-KK-2019-00007"]}]},{"name":"Consolidator Researcher program of \u00d3buda University","award":["TKP2021-NKTA-36"],"award-info":[{"award-number":["TKP2021-NKTA-36"]}]},{"name":"Consolidator Researcher program of \u00d3buda University","award":["\u00daNKP-21-3"],"award-info":[{"award-number":["\u00daNKP-21-3"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Non-coordinated physical activity may lead to hypoglycemia, which is a dangerous condition for diabetic people. Decision support systems related to type 1 diabetes mellitus (T1DM) still lack the capability of automated therapy modification by recognizing and categorizing the physical activity. Further, this desired adaptive therapy should be achieved without increasing the administrative load, which is already high for the diabetic community. These requirements can be satisfied by using artificial intelligence-based solutions, signals collected by wearable devices, and relying on the already available data sources, such as continuous glucose monitoring systems. In this work, we focus on the detection of physical activity by using a continuous glucose monitoring system and a wearable sensor providing the heart rate\u2014the latter is accessible even in the cheapest wearables. Our results show that the detection of physical activity is possible based on these data sources, even if only low-complexity artificial intelligence models are deployed. In general, our models achieved approximately 90% accuracy in the detection of physical activity.<\/jats:p>","DOI":"10.3390\/s22218568","type":"journal-article","created":{"date-parts":[[2022,11,8]],"date-time":"2022-11-08T08:17:12Z","timestamp":1667895432000},"page":"8568","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Detection of Physical Activity Using Machine Learning Methods Based on Continuous Blood Glucose Monitoring and Heart Rate Signals"],"prefix":"10.3390","volume":"22","author":[{"given":"Lehel","family":"D\u00e9nes-Fazakas","sequence":"first","affiliation":[{"name":"Physiological Controls Research Center, \u00d3buda University, B\u00e9csi \u00fat 96\/b, H-1034 Budapest, Hungary"},{"name":"Applied Informatics and Applied Mathematics Doctoral School, \u00d3buda University, B\u00e9csi \u00fat 96\/b, H-1034 Budapest, Hungary"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4425-5588","authenticated-orcid":false,"given":"M\u00e1t\u00e9","family":"Siket","sequence":"additional","affiliation":[{"name":"Physiological Controls Research Center, \u00d3buda University, B\u00e9csi \u00fat 96\/b, H-1034 Budapest, Hungary"},{"name":"Applied Informatics and Applied Mathematics Doctoral School, \u00d3buda University, B\u00e9csi \u00fat 96\/b, H-1034 Budapest, Hungary"},{"name":"Institute for Computer Science and Control, E\u00f6tv\u00f6s L\u00f3r\u00e1nd Research Network, H-1111 Budapest, Hungary"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6722-2642","authenticated-orcid":false,"given":"L\u00e1szl\u00f3","family":"Szil\u00e1gyi","sequence":"additional","affiliation":[{"name":"Physiological Controls Research Center, \u00d3buda University, B\u00e9csi \u00fat 96\/b, H-1034 Budapest, Hungary"},{"name":"Biomatics and Applied Artificial Intelligence Institution, John von Neumann Faculty of Informatics, \u00d3buda University, B\u00e9csi \u00fat 96\/b, H-1034 Budapest, Hungary"},{"name":"Computational Intelligence Research Group, Sapientia Hungarian University of Transylvania, 540485 T\u00eergu Mure\u015f, Romania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3188-0800","authenticated-orcid":false,"given":"Levente","family":"Kov\u00e1cs","sequence":"additional","affiliation":[{"name":"Physiological Controls Research Center, \u00d3buda University, B\u00e9csi \u00fat 96\/b, H-1034 Budapest, Hungary"},{"name":"Biomatics and Applied Artificial Intelligence Institution, John von Neumann Faculty of Informatics, \u00d3buda University, B\u00e9csi \u00fat 96\/b, H-1034 Budapest, Hungary"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8038-2210","authenticated-orcid":false,"given":"Gy\u00f6rgy","family":"Eigner","sequence":"additional","affiliation":[{"name":"Physiological Controls Research Center, \u00d3buda University, B\u00e9csi \u00fat 96\/b, H-1034 Budapest, Hungary"},{"name":"Biomatics and Applied Artificial Intelligence Institution, John von Neumann Faculty of Informatics, \u00d3buda University, B\u00e9csi \u00fat 96\/b, H-1034 Budapest, Hungary"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"546","DOI":"10.1002\/pro.2858","article-title":"GLUT, SGLT, and SWEET: Structural and mechanistic investigations of the glucose transporters","volume":"25","author":"Deng","year":"2016","journal-title":"Protein Sci."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Holt, R.I., Cockram, C., Flyvbjerg, A., and Goldstein, B.J. 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