Silvia Panicacci, Gianluca Giuffrida, M. Donati, Alberto Lubrano, Martina Olivelli, Alessio Ruiu, L. Fanucci
{"title":"利用全球卫星导航系统技术和聚类算法增强远程医疗平台支持流行病学分析","authors":"Silvia Panicacci, Gianluca Giuffrida, M. Donati, Alberto Lubrano, Martina Olivelli, Alessio Ruiu, L. Fanucci","doi":"10.1109/ICETCI53161.2021.9563621","DOIUrl":null,"url":null,"abstract":"Telemedicine platforms have been largely used to manage multiple problems during the Covid-19 pandemic. In fact, they have given the possibility of remotely monitoring infected and high-risk patients, reducing hospitalisations. Telemonitoring systems with Global Navigation Satellite System technology allow to geo-localise all patients' measurements and enable the tracking of positions. These data can be used for contact tracing or to support doctors in epidemiological analysis. This paper presents the integration of satellite technologies in an existing telemedicine system (E@syCare), during the current outbreak. In particular, the platform has been enhanced with GPS, to geo-tag all vital parameters collected by the tablet gateway and the smartwatch. Geographical data are processed, after a request through the improved web-based medical interface based on some filters (e.g., vital parameters and their thresholds, considered period of time, and maximum cluster radius), with two sequential clustering algorithms. Agglomerative Clustering is used to find the optimal number of clusters given a maximum radius, and K-Means to effectively generate the predefined number of clusters. Resulting clusters are shown on an interactive epidemiological map in the web-based medical interface. This additional feature gives the possibility to healthcare authorities to correlate the spread of a disease or a virus with specific geographical areas or environmental conditions, to monitor fitness/movement habits of patients (also when the pandemic is over), and to track contact among patients.","PeriodicalId":170858,"journal":{"name":"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Enhancing a Telemedicine Platform with Global Navigation Satellite System Technology and Clustering Algorithms for Supporting Epidemiological Analysis\",\"authors\":\"Silvia Panicacci, Gianluca Giuffrida, M. Donati, Alberto Lubrano, Martina Olivelli, Alessio Ruiu, L. 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Geographical data are processed, after a request through the improved web-based medical interface based on some filters (e.g., vital parameters and their thresholds, considered period of time, and maximum cluster radius), with two sequential clustering algorithms. Agglomerative Clustering is used to find the optimal number of clusters given a maximum radius, and K-Means to effectively generate the predefined number of clusters. Resulting clusters are shown on an interactive epidemiological map in the web-based medical interface. This additional feature gives the possibility to healthcare authorities to correlate the spread of a disease or a virus with specific geographical areas or environmental conditions, to monitor fitness/movement habits of patients (also when the pandemic is over), and to track contact among patients.\",\"PeriodicalId\":170858,\"journal\":{\"name\":\"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)\",\"volume\":\"174 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICETCI53161.2021.9563621\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Electronic Technology, Communication and Information (ICETCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICETCI53161.2021.9563621","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Enhancing a Telemedicine Platform with Global Navigation Satellite System Technology and Clustering Algorithms for Supporting Epidemiological Analysis
Telemedicine platforms have been largely used to manage multiple problems during the Covid-19 pandemic. In fact, they have given the possibility of remotely monitoring infected and high-risk patients, reducing hospitalisations. Telemonitoring systems with Global Navigation Satellite System technology allow to geo-localise all patients' measurements and enable the tracking of positions. These data can be used for contact tracing or to support doctors in epidemiological analysis. This paper presents the integration of satellite technologies in an existing telemedicine system (E@syCare), during the current outbreak. In particular, the platform has been enhanced with GPS, to geo-tag all vital parameters collected by the tablet gateway and the smartwatch. Geographical data are processed, after a request through the improved web-based medical interface based on some filters (e.g., vital parameters and their thresholds, considered period of time, and maximum cluster radius), with two sequential clustering algorithms. Agglomerative Clustering is used to find the optimal number of clusters given a maximum radius, and K-Means to effectively generate the predefined number of clusters. Resulting clusters are shown on an interactive epidemiological map in the web-based medical interface. This additional feature gives the possibility to healthcare authorities to correlate the spread of a disease or a virus with specific geographical areas or environmental conditions, to monitor fitness/movement habits of patients (also when the pandemic is over), and to track contact among patients.