Michael Mitchell, Frank Sposaro, Annie Wang, Gary S. Tyson
{"title":"BEAT: Bio-Environmental Android Tracking","authors":"Michael Mitchell, Frank Sposaro, Annie Wang, Gary S. Tyson","doi":"10.1109/RWS.2011.5725489","DOIUrl":null,"url":null,"abstract":"We introduce BEAT (Bio-Environmental Android Tracking), which provides methods for collecting, processing, and archiving one's daily vital and spatiotemporal statistics using off-the-shelf wireless devices and biologic and environmental sensors. BEAT can operate in a self-contained manner on a mobile device and analyze vital information in real time. It uses statistics such as heartbeat variance and range thresholds to issue alerts. Alerts are propagated in a tiered fashion, so that the end user and his/her social contacts have a chance to detect false alerts before contacting medical professionals. BEAT is built on the open Android platform to support a diverse class of mobile devices. The framework can be extended to a full-fledged personal health monitoring system by incorporating additional biosensor data such as blood pressure, glucose, and weight.","PeriodicalId":250672,"journal":{"name":"2011 IEEE Radio and Wireless Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE Radio and Wireless Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RWS.2011.5725489","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18
Abstract
We introduce BEAT (Bio-Environmental Android Tracking), which provides methods for collecting, processing, and archiving one's daily vital and spatiotemporal statistics using off-the-shelf wireless devices and biologic and environmental sensors. BEAT can operate in a self-contained manner on a mobile device and analyze vital information in real time. It uses statistics such as heartbeat variance and range thresholds to issue alerts. Alerts are propagated in a tiered fashion, so that the end user and his/her social contacts have a chance to detect false alerts before contacting medical professionals. BEAT is built on the open Android platform to support a diverse class of mobile devices. The framework can be extended to a full-fledged personal health monitoring system by incorporating additional biosensor data such as blood pressure, glucose, and weight.