实时可穿戴设备,用于预测长期covid患者的病情

AbdelRahman Tamer AbdelGawad, S. Toha, Nor Hidayati, Diyana Nordin, Ahmad Syahrin Idris
{"title":"实时可穿戴设备,用于预测长期covid患者的病情","authors":"AbdelRahman Tamer AbdelGawad, S. Toha, Nor Hidayati, Diyana Nordin, Ahmad Syahrin Idris","doi":"10.1049/icp.2022.2279","DOIUrl":null,"url":null,"abstract":": This paper aims to develop a wearable device that can be able to Predict the long covid-19 patients’ conditions, to notify the doctors on a real-time basis. Long covid-19 patients suffer a lot during their daily activities especially if the lasting symptom is related to the respiratory system. By developing a system, that is easy and comfortable to wear during normal daily life, we believe that we will be able to predict the long covid-19 patients’ condition. The system should first detect and analyze the patient’s breathing pattern using artificial intelligence then store the patient’s breathing pattern along with his status in an online database, then notify the doctors in case of a critical situation. To train the model the breathing pattern of current long covid patients and normal people was captured during doing daily activities such as walking, sitting, and climbing stairs. We hope that the developed system will help in easing the suffering of long covid patients by providing better monitoring of their health.","PeriodicalId":170898,"journal":{"name":"8th International Conference on Mechatronics Engineering (ICOM 2022)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Real-time wearable device for predicting a long covid patient's condition\",\"authors\":\"AbdelRahman Tamer AbdelGawad, S. Toha, Nor Hidayati, Diyana Nordin, Ahmad Syahrin Idris\",\"doi\":\"10.1049/icp.2022.2279\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": This paper aims to develop a wearable device that can be able to Predict the long covid-19 patients’ conditions, to notify the doctors on a real-time basis. Long covid-19 patients suffer a lot during their daily activities especially if the lasting symptom is related to the respiratory system. By developing a system, that is easy and comfortable to wear during normal daily life, we believe that we will be able to predict the long covid-19 patients’ condition. The system should first detect and analyze the patient’s breathing pattern using artificial intelligence then store the patient’s breathing pattern along with his status in an online database, then notify the doctors in case of a critical situation. To train the model the breathing pattern of current long covid patients and normal people was captured during doing daily activities such as walking, sitting, and climbing stairs. We hope that the developed system will help in easing the suffering of long covid patients by providing better monitoring of their health.\",\"PeriodicalId\":170898,\"journal\":{\"name\":\"8th International Conference on Mechatronics Engineering (ICOM 2022)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"8th International Conference on Mechatronics Engineering (ICOM 2022)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1049/icp.2022.2279\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"8th International Conference on Mechatronics Engineering (ICOM 2022)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/icp.2022.2279","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

:本文旨在开发一种可穿戴设备,能够预测covid-19患者的长期病情,实时通知医生。长期covid-19患者在日常活动中遭受很大痛苦,特别是如果持续症状与呼吸系统有关。通过开发一种在日常生活中佩戴方便舒适的系统,我们相信我们将能够预测covid-19患者的长期病情。该系统应首先使用人工智能检测和分析患者的呼吸模式,然后将患者的呼吸模式及其状态存储在在线数据库中,然后在紧急情况下通知医生。为了训练模型,研究人员在日常活动(如走路、坐着和爬楼梯)中捕捉了当前长期covid - 19患者和正常人的呼吸模式。我们希望开发的系统能够通过更好地监测长期患者的健康状况,帮助减轻他们的痛苦。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Real-time wearable device for predicting a long covid patient's condition
: This paper aims to develop a wearable device that can be able to Predict the long covid-19 patients’ conditions, to notify the doctors on a real-time basis. Long covid-19 patients suffer a lot during their daily activities especially if the lasting symptom is related to the respiratory system. By developing a system, that is easy and comfortable to wear during normal daily life, we believe that we will be able to predict the long covid-19 patients’ condition. The system should first detect and analyze the patient’s breathing pattern using artificial intelligence then store the patient’s breathing pattern along with his status in an online database, then notify the doctors in case of a critical situation. To train the model the breathing pattern of current long covid patients and normal people was captured during doing daily activities such as walking, sitting, and climbing stairs. We hope that the developed system will help in easing the suffering of long covid patients by providing better monitoring of their health.
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
期刊最新文献
Deep learning based prediction model of recurrent pedal pressing for low speed Agile Enterprise Geographic Information System (AEGIS) from design and development perspective Visual detection of biofouling using Hue-Saturation-Value (HSV) colour for ship hull cleaning robot Development of an angle sensor using optical polarizer Ventilation monitoring system to improve indoor air quality in shared spaces
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1