B. Venema, Matthias Simon Wolke, V. Blazek, S. Leonhardt
{"title":"用于移动健康监测的功耗优化反射式耳内脉搏血氧仪","authors":"B. Venema, Matthias Simon Wolke, V. Blazek, S. Leonhardt","doi":"10.1109/BIOWIRELESS.2014.6827738","DOIUrl":null,"url":null,"abstract":"An unobtrusive, mobile in-ear pulse oximeter for body sensor network with predictive power-management optimization algorithm is presented. The system can be connected via Bluetooth to a smartphone for online visualization of vital signs, recording or telemonitoring via UMTS (Universal Mobile Telecommunications System). The work focuses on energy saving strategies. Main part of the work is a significant reduction of the PPG-on-time by means of a real-time heart rate estimation routine. The concept is tested on sleep apnea patients with 96.8 % correct estimated heart events at a mean power consumption of 103 mW.","PeriodicalId":341652,"journal":{"name":"2014 IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems (BioWireleSS)","volume":"40 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A power consumption optimized reflective in-ear pulse oximeter for mobile health monitoring\",\"authors\":\"B. Venema, Matthias Simon Wolke, V. Blazek, S. Leonhardt\",\"doi\":\"10.1109/BIOWIRELESS.2014.6827738\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An unobtrusive, mobile in-ear pulse oximeter for body sensor network with predictive power-management optimization algorithm is presented. The system can be connected via Bluetooth to a smartphone for online visualization of vital signs, recording or telemonitoring via UMTS (Universal Mobile Telecommunications System). The work focuses on energy saving strategies. Main part of the work is a significant reduction of the PPG-on-time by means of a real-time heart rate estimation routine. The concept is tested on sleep apnea patients with 96.8 % correct estimated heart events at a mean power consumption of 103 mW.\",\"PeriodicalId\":341652,\"journal\":{\"name\":\"2014 IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems (BioWireleSS)\",\"volume\":\"40 4\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems (BioWireleSS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIOWIRELESS.2014.6827738\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Topical Conference on Biomedical Wireless Technologies, Networks, and Sensing Systems (BioWireleSS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIOWIRELESS.2014.6827738","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A power consumption optimized reflective in-ear pulse oximeter for mobile health monitoring
An unobtrusive, mobile in-ear pulse oximeter for body sensor network with predictive power-management optimization algorithm is presented. The system can be connected via Bluetooth to a smartphone for online visualization of vital signs, recording or telemonitoring via UMTS (Universal Mobile Telecommunications System). The work focuses on energy saving strategies. Main part of the work is a significant reduction of the PPG-on-time by means of a real-time heart rate estimation routine. The concept is tested on sleep apnea patients with 96.8 % correct estimated heart events at a mean power consumption of 103 mW.