{"title":"Metabolic activity monitoring in a telehealthcare system for chronic patients","authors":"M. Prado, L. Roa, J. Reina-Tosina","doi":"10.1109/HEALTH.2003.1218722","DOIUrl":null,"url":null,"abstract":"The virtual center for renal support (VCRS) is a novel telehealthcare system based on a hybrid approach for signal processing and knowledge discovering. It is featured by the addition of a new signal processing layer to the more classical telehealthcare computational architectures. This layer is a realtime simulator composed by customized dynamics models, which represent kinetic and physiological aspects of the patient renal system. A second layer based on more classical data driven algorithms follows to the simulator-based layer. This approach combines the higher predictive capability of dynamics models with the demonstrated accuracy of data driven models.","PeriodicalId":159453,"journal":{"name":"Proceedings 5th International Workshop on Enterprise Networking and Computing in Healthcare Industry (HealthCom)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 5th International Workshop on Enterprise Networking and Computing in Healthcare Industry (HealthCom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HEALTH.2003.1218722","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The virtual center for renal support (VCRS) is a novel telehealthcare system based on a hybrid approach for signal processing and knowledge discovering. It is featured by the addition of a new signal processing layer to the more classical telehealthcare computational architectures. This layer is a realtime simulator composed by customized dynamics models, which represent kinetic and physiological aspects of the patient renal system. A second layer based on more classical data driven algorithms follows to the simulator-based layer. This approach combines the higher predictive capability of dynamics models with the demonstrated accuracy of data driven models.