雾驱动的物联网电子健康框架,用于监测和控制哮喘恶化

A. Maach, J. Alami, E. E. Mazoudi
{"title":"雾驱动的物联网电子健康框架,用于监测和控制哮喘恶化","authors":"A. Maach, J. Alami, E. E. Mazoudi","doi":"10.1109/wincom47513.2019.8942540","DOIUrl":null,"url":null,"abstract":"About 339 million people worldwide suffer from asthma, one of the most common chronic diseases among children and adults. The World Asthma Burden Report 2018 reveals that 1,000 people die of asthma every day, which is of great concern because many of these deaths are preventable in an early stage of asthma, especially in low- and middle-income countries where the majority of people do not have access to high quality medical care and medicines. Recently, the use of fog-based health care support systems has proven to be an effective solution for continuous remote monitoring of patient's health, with the benefits of a high quality of life for patients and disease control. In this paper, a framework based on fog and the Internet of Things is proposed to assess the severity of asthma and prevent the risk of asthma exacerbation in this regard, an artificial neural network has been used. Experimental results reveal a high level of accuracy in predicting the risk of asthma exacerbation, and alerts are sent to patients and caregivers in order to control the asthma disease.","PeriodicalId":222207,"journal":{"name":"2019 International Conference on Wireless Networks and Mobile Communications (WINCOM)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A fog-driven IoT e-Health framework to monitor and control Asthma Exacerbation\",\"authors\":\"A. Maach, J. Alami, E. E. Mazoudi\",\"doi\":\"10.1109/wincom47513.2019.8942540\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"About 339 million people worldwide suffer from asthma, one of the most common chronic diseases among children and adults. The World Asthma Burden Report 2018 reveals that 1,000 people die of asthma every day, which is of great concern because many of these deaths are preventable in an early stage of asthma, especially in low- and middle-income countries where the majority of people do not have access to high quality medical care and medicines. Recently, the use of fog-based health care support systems has proven to be an effective solution for continuous remote monitoring of patient's health, with the benefits of a high quality of life for patients and disease control. In this paper, a framework based on fog and the Internet of Things is proposed to assess the severity of asthma and prevent the risk of asthma exacerbation in this regard, an artificial neural network has been used. Experimental results reveal a high level of accuracy in predicting the risk of asthma exacerbation, and alerts are sent to patients and caregivers in order to control the asthma disease.\",\"PeriodicalId\":222207,\"journal\":{\"name\":\"2019 International Conference on Wireless Networks and Mobile Communications (WINCOM)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Wireless Networks and Mobile Communications (WINCOM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/wincom47513.2019.8942540\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Wireless Networks and Mobile Communications (WINCOM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/wincom47513.2019.8942540","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

全世界约有3.39亿人患有哮喘,这是儿童和成人中最常见的慢性疾病之一。《2018年世界哮喘负担报告》显示,每天有1000人死于哮喘,这令人极为关切,因为其中许多死亡在哮喘早期阶段是可以预防的,特别是在大多数人无法获得高质量医疗保健和药物的低收入和中等收入国家。最近,使用基于雾的医疗保健支持系统已被证明是一种有效的解决方案,可以持续远程监测患者的健康状况,并为患者提供高质量的生活和疾病控制。本文提出了一个基于雾和物联网的框架来评估哮喘的严重程度并预防哮喘加重的风险,在这方面使用了人工神经网络。实验结果表明,在预测哮喘恶化风险方面具有很高的准确性,并向患者和护理人员发送警报,以控制哮喘疾病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A fog-driven IoT e-Health framework to monitor and control Asthma Exacerbation
About 339 million people worldwide suffer from asthma, one of the most common chronic diseases among children and adults. The World Asthma Burden Report 2018 reveals that 1,000 people die of asthma every day, which is of great concern because many of these deaths are preventable in an early stage of asthma, especially in low- and middle-income countries where the majority of people do not have access to high quality medical care and medicines. Recently, the use of fog-based health care support systems has proven to be an effective solution for continuous remote monitoring of patient's health, with the benefits of a high quality of life for patients and disease control. In this paper, a framework based on fog and the Internet of Things is proposed to assess the severity of asthma and prevent the risk of asthma exacerbation in this regard, an artificial neural network has been used. Experimental results reveal a high level of accuracy in predicting the risk of asthma exacerbation, and alerts are sent to patients and caregivers in order to control the asthma disease.
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