Analysis Algorithm of Biomedical Signals in Remote Monitoring Systems of Human Health

A. Osipov, A. V. Patseev, S. Patseev
{"title":"Analysis Algorithm of Biomedical Signals in Remote Monitoring Systems of Human Health","authors":"A. Osipov, A. V. Patseev, S. Patseev","doi":"10.35596/1729-7648-2023-21-1-5-11","DOIUrl":null,"url":null,"abstract":"The article considers the problems of adaptation of existing and development of new diagnostic algorithms and methods of remote monitoring of the physiological state of a person in relation to the Internet of Things technology. In order to reduce the energy consumption of the wearable unit and biomedical signal sensors, reduce the redundancy of the recorded and transmitted diagnostic information, the critical situation recognition process is divided into two stages. At the first stage, the main indicators (heart rate and human fall signal) are monitored. If they do not comply with the norm, additional signals are analyzed (the second stage) to confirm the critical situa tion and determine the degree of alarm.","PeriodicalId":33565,"journal":{"name":"Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioelektroniki","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioelektroniki","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35596/1729-7648-2023-21-1-5-11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The article considers the problems of adaptation of existing and development of new diagnostic algorithms and methods of remote monitoring of the physiological state of a person in relation to the Internet of Things technology. In order to reduce the energy consumption of the wearable unit and biomedical signal sensors, reduce the redundancy of the recorded and transmitted diagnostic information, the critical situation recognition process is divided into two stages. At the first stage, the main indicators (heart rate and human fall signal) are monitored. If they do not comply with the norm, additional signals are analyzed (the second stage) to confirm the critical situa tion and determine the degree of alarm.
人体健康远程监测系统中生物医学信号分析算法
本文考虑了与物联网技术相关的人的生理状态远程监测的新诊断算法和方法的适应和发展问题。为了降低可穿戴单元和生物医学信号传感器的能耗,减少记录和传输的诊断信息的冗余,关键情况识别过程分为两个阶段。在第一阶段,监测主要指标(心率和人体跌倒信号)。如果它们不符合规范,则对附加信号进行分析(第二阶段),以确认临界状态并确定警报程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
87
审稿时长
8 weeks
×
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