Juliano B. Prettz, J. P. J. D. Da Costa, J. Alvim, R. K. Miranda, M. Zanatta
{"title":"Efficient and low cost MIMO communication architecture for smartbands applied to postoperative patient care","authors":"Juliano B. Prettz, J. P. J. D. Da Costa, J. Alvim, R. K. Miranda, M. Zanatta","doi":"10.1109/RPC.2017.8168055","DOIUrl":null,"url":null,"abstract":"Frequently, postoperative patient care requires a long period of observation in hospitals by the medical board. During this observation period, the medical board manually inserts time to time vital information of the patients into the medical information system. Such manual procedure can be improved and become more reliable if the patients are equipped with wearable devices that allow the real-time data acquisition and the data processing by machine learning systems. In this work, we propose an efficient and low cost monitoring system for postoperative patient care based on commercial smartbands. Since the current smartbands are restricted to single input single output (SISO) communication, i.e. only one smartband can connect to one smartphone in a short distance range, we propose to expand the commercial smartband capability to a multiple input multiple output (MIMO) communication by proposing a new architecture based on a signal concentrator. According to our experimental results, our proposed architecture with a single concentrator allows a 248: N communication, i.e. the simultaneous usage of 248 smartbands in a same room and the data collected data is transmitted to any number N of physicians without distance restrictions. By considering a system with multiple concentrators, we also propose an M:N architecture communication for smartbands.","PeriodicalId":144625,"journal":{"name":"2017 Second Russia and Pacific Conference on Computer Technology and Applications (RPC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Second Russia and Pacific Conference on Computer Technology and Applications (RPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RPC.2017.8168055","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Frequently, postoperative patient care requires a long period of observation in hospitals by the medical board. During this observation period, the medical board manually inserts time to time vital information of the patients into the medical information system. Such manual procedure can be improved and become more reliable if the patients are equipped with wearable devices that allow the real-time data acquisition and the data processing by machine learning systems. In this work, we propose an efficient and low cost monitoring system for postoperative patient care based on commercial smartbands. Since the current smartbands are restricted to single input single output (SISO) communication, i.e. only one smartband can connect to one smartphone in a short distance range, we propose to expand the commercial smartband capability to a multiple input multiple output (MIMO) communication by proposing a new architecture based on a signal concentrator. According to our experimental results, our proposed architecture with a single concentrator allows a 248: N communication, i.e. the simultaneous usage of 248 smartbands in a same room and the data collected data is transmitted to any number N of physicians without distance restrictions. By considering a system with multiple concentrators, we also propose an M:N architecture communication for smartbands.