C. O. Rolim, F. Koch, Carlos Becker Westphall, Jorge Werner, A. Fracalossi, Giovanni Schmitt Salvador
{"title":"A Cloud Computing Solution for Patient's Data Collection in Health Care Institutions","authors":"C. O. Rolim, F. Koch, Carlos Becker Westphall, Jorge Werner, A. Fracalossi, Giovanni Schmitt Salvador","doi":"10.1109/eTELEMED.2010.19","DOIUrl":null,"url":null,"abstract":"Existing processes for patients' vital data collection require a great deal of labor work to collect, input and analyze the information. These processes are usually slow and error-prone, introducing a latency that prevents real-time data accessibility. This scenario restrains the clinical diagnostics and monitoring capabilities. We propose a solution to automate this process by using “sensors” attached to existing medical equipments that are inter-connected to exchange service. The proposal is based on the concepts of utility computing and wireless sensor networks. The information becomes available in the “cloud” from where it can be processed by expert systems and/or distributed to medical staff. The proof-of-concept design applies commodity computing integrated to legacy medical devices, ensuring cost-effectiveness and simple integration.","PeriodicalId":213702,"journal":{"name":"2010 Second International Conference on eHealth, Telemedicine, and Social Medicine","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"438","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Second International Conference on eHealth, Telemedicine, and Social Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/eTELEMED.2010.19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 438
Abstract
Existing processes for patients' vital data collection require a great deal of labor work to collect, input and analyze the information. These processes are usually slow and error-prone, introducing a latency that prevents real-time data accessibility. This scenario restrains the clinical diagnostics and monitoring capabilities. We propose a solution to automate this process by using “sensors” attached to existing medical equipments that are inter-connected to exchange service. The proposal is based on the concepts of utility computing and wireless sensor networks. The information becomes available in the “cloud” from where it can be processed by expert systems and/or distributed to medical staff. The proof-of-concept design applies commodity computing integrated to legacy medical devices, ensuring cost-effectiveness and simple integration.