海报:听到你的呼吸:使用智能手机进行细致的睡眠监测

Yanzhi Ren, Chen Wang, Yingying Chen, J. Yang
{"title":"海报:听到你的呼吸:使用智能手机进行细致的睡眠监测","authors":"Yanzhi Ren, Chen Wang, Yingying Chen, J. Yang","doi":"10.1145/2639108.2642898","DOIUrl":null,"url":null,"abstract":"Sleep monitoring has drawn increasingly attention as the quality and quantity of the sleep are important for maintaining a person's health and well-being. For example, inadequate and irregular sleep are usually associated with serious health problems such as fatigue, depression and cardiovascular disease. Traditional sleep monitoring systems, such as PSG, involve wearable sensors with professional installations, and thus are limited to clinical usage. Recent work in using smartphone sensors for sleep monitoring can detect several events related to sleep, such as body movement, cough and snore. Such coarse-grained sleep monitoring however is unable to detect the breathing rate which is a vital sign and health indicator. This work presents a fine-grained sleep monitoring system which is capable of detecting the breathing rate by leveraging smartphones. Our system exploits the readily available smartphone earphone that placed close to the user to capture the breath sound reliably. Given the captured acoustic signal, our system performs noise reduction to remove environmental noise and then identifies the breathing rate based on the signal envelope detection. Our experimental evaluation of six subjects over six months time period demonstrates that the breathing rate monitoring is highly accurate and robust under various environments. This strongly indicates the feasibility of using the smartphone and its earphone to perform continuous and noninvasive fine-grained sleep monitoring.","PeriodicalId":331897,"journal":{"name":"Proceedings of the 20th annual international conference on Mobile computing and networking","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Poster: hearing your breathing: fine-grained sleep monitoring using smartphones\",\"authors\":\"Yanzhi Ren, Chen Wang, Yingying Chen, J. Yang\",\"doi\":\"10.1145/2639108.2642898\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sleep monitoring has drawn increasingly attention as the quality and quantity of the sleep are important for maintaining a person's health and well-being. For example, inadequate and irregular sleep are usually associated with serious health problems such as fatigue, depression and cardiovascular disease. Traditional sleep monitoring systems, such as PSG, involve wearable sensors with professional installations, and thus are limited to clinical usage. Recent work in using smartphone sensors for sleep monitoring can detect several events related to sleep, such as body movement, cough and snore. Such coarse-grained sleep monitoring however is unable to detect the breathing rate which is a vital sign and health indicator. This work presents a fine-grained sleep monitoring system which is capable of detecting the breathing rate by leveraging smartphones. Our system exploits the readily available smartphone earphone that placed close to the user to capture the breath sound reliably. Given the captured acoustic signal, our system performs noise reduction to remove environmental noise and then identifies the breathing rate based on the signal envelope detection. Our experimental evaluation of six subjects over six months time period demonstrates that the breathing rate monitoring is highly accurate and robust under various environments. This strongly indicates the feasibility of using the smartphone and its earphone to perform continuous and noninvasive fine-grained sleep monitoring.\",\"PeriodicalId\":331897,\"journal\":{\"name\":\"Proceedings of the 20th annual international conference on Mobile computing and networking\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 20th annual international conference on Mobile computing and networking\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2639108.2642898\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 20th annual international conference on Mobile computing and networking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2639108.2642898","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14

摘要

由于睡眠的质量和数量对维持一个人的健康和幸福至关重要,睡眠监测越来越受到人们的关注。例如,睡眠不足和不规律通常与严重的健康问题有关,如疲劳、抑郁和心血管疾病。传统的睡眠监测系统,如PSG,涉及专业安装的可穿戴传感器,因此仅限于临床使用。最近使用智能手机传感器进行睡眠监测的工作可以检测到与睡眠有关的几个事件,如身体运动、咳嗽和打鼾。然而,这种粗粒度的睡眠监测无法检测到呼吸频率这一生命体征和健康指标。这项工作提出了一种精细的睡眠监测系统,能够利用智能手机检测呼吸频率。我们的系统利用随时可用的智能手机耳机,放置在用户附近,可靠地捕捉呼吸声音。给定捕获的声信号,我们的系统执行降噪以消除环境噪声,然后根据信号包络检测识别呼吸速率。我们对6名受试者6个月时间的实验评估表明,在各种环境下呼吸频率监测是高度准确和稳健的。这有力地表明,使用智能手机及其耳机进行连续、无创的细粒度睡眠监测是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Poster: hearing your breathing: fine-grained sleep monitoring using smartphones
Sleep monitoring has drawn increasingly attention as the quality and quantity of the sleep are important for maintaining a person's health and well-being. For example, inadequate and irregular sleep are usually associated with serious health problems such as fatigue, depression and cardiovascular disease. Traditional sleep monitoring systems, such as PSG, involve wearable sensors with professional installations, and thus are limited to clinical usage. Recent work in using smartphone sensors for sleep monitoring can detect several events related to sleep, such as body movement, cough and snore. Such coarse-grained sleep monitoring however is unable to detect the breathing rate which is a vital sign and health indicator. This work presents a fine-grained sleep monitoring system which is capable of detecting the breathing rate by leveraging smartphones. Our system exploits the readily available smartphone earphone that placed close to the user to capture the breath sound reliably. Given the captured acoustic signal, our system performs noise reduction to remove environmental noise and then identifies the breathing rate based on the signal envelope detection. Our experimental evaluation of six subjects over six months time period demonstrates that the breathing rate monitoring is highly accurate and robust under various environments. This strongly indicates the feasibility of using the smartphone and its earphone to perform continuous and noninvasive fine-grained sleep monitoring.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信