{"title":"Human health control monitor system using smart mobiles: Context changes dependent human behavior","authors":"Ashok Senthil Kumar, Subash Chandar, PG Students","doi":"10.1109/ICONSTEM.2016.7560928","DOIUrl":null,"url":null,"abstract":"A Human health control monitor system (HHCMSes) is a mobile medical application is used to detect continuous monitoring and manage the human body blood glucoses levels. HHCMS promises to give to extend the life period of human being. HHCMSes is a testing device very efficient to monitor the glucoses levels. Sensor can wear anywhere in our human body as like as wrist watches. A sensor connects to smart phones using HHCMSes software. Once connected this software continuously to monitor the blood glucoses levels in our body. In our body, when change the glucose levels is to intimate through smart mobile phones. HHCMS is easily to monitor the indoor and outdoor physical movement of blood levels changing often in our body. Existing approaches uses moment generate function (MGF) is support only statistical method of gathering the value, reviewing the value, survey the value, and give an interpreting the variable of numerical data, cannot identifying the transfer function between sensor and mobiles. In this paper, we can propose robust compatible, so we can uses Mason's gain formula (MGF) is a process to detect the transfer function by using linear signal-flow graph (SFG) and cyebyshev's theorem and Markov theorem uses to find out the desired result of HHCMSes.","PeriodicalId":256750,"journal":{"name":"2016 Second International Conference on Science Technology Engineering and Management (ICONSTEM)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Second International Conference on Science Technology Engineering and Management (ICONSTEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICONSTEM.2016.7560928","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
A Human health control monitor system (HHCMSes) is a mobile medical application is used to detect continuous monitoring and manage the human body blood glucoses levels. HHCMS promises to give to extend the life period of human being. HHCMSes is a testing device very efficient to monitor the glucoses levels. Sensor can wear anywhere in our human body as like as wrist watches. A sensor connects to smart phones using HHCMSes software. Once connected this software continuously to monitor the blood glucoses levels in our body. In our body, when change the glucose levels is to intimate through smart mobile phones. HHCMS is easily to monitor the indoor and outdoor physical movement of blood levels changing often in our body. Existing approaches uses moment generate function (MGF) is support only statistical method of gathering the value, reviewing the value, survey the value, and give an interpreting the variable of numerical data, cannot identifying the transfer function between sensor and mobiles. In this paper, we can propose robust compatible, so we can uses Mason's gain formula (MGF) is a process to detect the transfer function by using linear signal-flow graph (SFG) and cyebyshev's theorem and Markov theorem uses to find out the desired result of HHCMSes.