{"title":"Wi-Sleep: Contactless Sleep Monitoring via WiFi Signals","authors":"Xuefeng Liu, Jiannong Cao, Shaojie Tang, Jiaqi Wen","doi":"10.1109/RTSS.2014.30","DOIUrl":null,"url":null,"abstract":"Is it possible to leverage WiFi signals collected in bedrooms to monitor a person's sleep? In this paper, we show that with off-the-shelf WiFi devices, fine-grained sleep information like a person's respiration, sleeping postures and rollovers can be successfully extracted. We do this by introducing Wi-Sleep, the first sleep monitoring system based on WiFi signals. Wi-Sleep adopts off-the-shelf WiFi devices to continuously collect the fine-grained wireless channel state information (CSI) around a person. From the CSI, Wi-Sleep extracts rhythmic patterns associated with respiration and abrupt changes due to the body movement. Compared to existing sleep monitoring systems that usually require special devices attached to human body (i.e. Probes, head belt, and wrist band), Wi-Sleep is completely contact less. In addition, different from many vision-based sleep monitoring systems, Wi-Sleep is robust to low-light environments and does not raise privacy concerns. Preliminary testing results show that the Wi-Sleep can reliably track a person's respiration and sleeping postures in different conditions.","PeriodicalId":353167,"journal":{"name":"2014 IEEE Real-Time Systems Symposium","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"256","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Real-Time Systems Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTSS.2014.30","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 256
Abstract
Is it possible to leverage WiFi signals collected in bedrooms to monitor a person's sleep? In this paper, we show that with off-the-shelf WiFi devices, fine-grained sleep information like a person's respiration, sleeping postures and rollovers can be successfully extracted. We do this by introducing Wi-Sleep, the first sleep monitoring system based on WiFi signals. Wi-Sleep adopts off-the-shelf WiFi devices to continuously collect the fine-grained wireless channel state information (CSI) around a person. From the CSI, Wi-Sleep extracts rhythmic patterns associated with respiration and abrupt changes due to the body movement. Compared to existing sleep monitoring systems that usually require special devices attached to human body (i.e. Probes, head belt, and wrist band), Wi-Sleep is completely contact less. In addition, different from many vision-based sleep monitoring systems, Wi-Sleep is robust to low-light environments and does not raise privacy concerns. Preliminary testing results show that the Wi-Sleep can reliably track a person's respiration and sleeping postures in different conditions.