移动医疗网络应急报警用户反馈系统

James Jin Kang
{"title":"移动医疗网络应急报警用户反馈系统","authors":"James Jin Kang","doi":"10.1145/3127942.3127964","DOIUrl":null,"url":null,"abstract":"Activity Recognition (AR), Internet of Things (IoT), and speech recognition are emerging technologies in the context of wearable devices and Mobile health (mHealth) networks. Applications of mHealth sensors on human bodies can involve the measurement of physiological data, and may be utilized to initiate an alarm in an emergency health situation. AR devices such as accelerometers may also be used for a similar application in determining the activity and posture status of the user. However, there is always the possibility of false alarms, and to avoid these occurrences, we propose a user feedback system for alarm confirmation via a smart device. As users may be unable to physically respond in some situations, such as a state of immobility from injury, this paper proposes to improve the user feedback system with a voice confirmation functionality utilizing speech recognition embedded within smart devices. The potentials of this user feedback system in mHealth can not only contribute towards improve the alarm accuracy, but may reduce the occurrence of false alarms. Its functionality can also be enhanced via real-time communication with their health service provider who can assess the user health status with the data from the sensors.","PeriodicalId":270425,"journal":{"name":"Proceedings of the 1st International Conference on Algorithms, Computing and Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"User Feedback System for Emergency Alarms in Mobile Health Networks\",\"authors\":\"James Jin Kang\",\"doi\":\"10.1145/3127942.3127964\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Activity Recognition (AR), Internet of Things (IoT), and speech recognition are emerging technologies in the context of wearable devices and Mobile health (mHealth) networks. Applications of mHealth sensors on human bodies can involve the measurement of physiological data, and may be utilized to initiate an alarm in an emergency health situation. AR devices such as accelerometers may also be used for a similar application in determining the activity and posture status of the user. However, there is always the possibility of false alarms, and to avoid these occurrences, we propose a user feedback system for alarm confirmation via a smart device. As users may be unable to physically respond in some situations, such as a state of immobility from injury, this paper proposes to improve the user feedback system with a voice confirmation functionality utilizing speech recognition embedded within smart devices. The potentials of this user feedback system in mHealth can not only contribute towards improve the alarm accuracy, but may reduce the occurrence of false alarms. Its functionality can also be enhanced via real-time communication with their health service provider who can assess the user health status with the data from the sensors.\",\"PeriodicalId\":270425,\"journal\":{\"name\":\"Proceedings of the 1st International Conference on Algorithms, Computing and Systems\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1st International Conference on Algorithms, Computing and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3127942.3127964\",\"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 1st International Conference on Algorithms, Computing and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3127942.3127964","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

活动识别(AR)、物联网(IoT)和语音识别是可穿戴设备和移动健康(mHealth)网络背景下的新兴技术。移动健康传感器在人体上的应用可涉及生理数据的测量,并可用于在紧急卫生情况下发出警报。AR设备如加速度计也可用于类似的应用,以确定用户的活动和姿势状态。然而,总是存在误报的可能性,为了避免这种情况的发生,我们提出了一种通过智能设备进行报警确认的用户反馈系统。由于用户在某些情况下可能无法做出身体反应,例如因受伤而无法移动的状态,因此本文建议利用智能设备内嵌入的语音识别功能,通过语音确认功能改进用户反馈系统。这种用户反馈系统在移动医疗中的潜力不仅有助于提高报警的准确性,而且可以减少误报的发生。它的功能还可以通过与健康服务提供商的实时通信来增强,后者可以利用传感器的数据评估用户的健康状况。
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
User Feedback System for Emergency Alarms in Mobile Health Networks
Activity Recognition (AR), Internet of Things (IoT), and speech recognition are emerging technologies in the context of wearable devices and Mobile health (mHealth) networks. Applications of mHealth sensors on human bodies can involve the measurement of physiological data, and may be utilized to initiate an alarm in an emergency health situation. AR devices such as accelerometers may also be used for a similar application in determining the activity and posture status of the user. However, there is always the possibility of false alarms, and to avoid these occurrences, we propose a user feedback system for alarm confirmation via a smart device. As users may be unable to physically respond in some situations, such as a state of immobility from injury, this paper proposes to improve the user feedback system with a voice confirmation functionality utilizing speech recognition embedded within smart devices. The potentials of this user feedback system in mHealth can not only contribute towards improve the alarm accuracy, but may reduce the occurrence of false alarms. Its functionality can also be enhanced via real-time communication with their health service provider who can assess the user health status with the data from the sensors.
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
Lying-Pig Detection using Depth Information Touching-Pigs Segmentation using Concave Points in Continuous Video Frames Automatic Nucleus Detection of Pap Smear Images using Stacked Sparse Autoencoder (SSAE) A New Approach for Recommender System Time Series Analysis and Crime Pattern Forecasting of City Crime Data
×
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