• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

面向实时医疗监测的自组织对等中间件。

Self-Organizing Peer-To-Peer Middleware for Healthcare Monitoring in Real-Time.

机构信息

School of Electronics Engineering, College of IT Engineering, Kyungpook National University, 80 Daehakro, Bukgu, Daegu 702-701, Korea.

Center of Self-Organizing Software-Platform, Kyungpook National University, 80 Daehakro, Bukgu, Daegu 702-701, Korea.

出版信息

Sensors (Basel). 2017 Nov 17;17(11):2650. doi: 10.3390/s17112650.

DOI:10.3390/s17112650
PMID:29149045
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5713001/
Abstract

As the number of elderly persons with chronic illnesses increases, a new public infrastructure for their care is becoming increasingly necessary. In particular, technologies that can monitoring bio-signals in real-time have been receiving significant attention. Currently, most healthcare monitoring services are implemented by wireless carrier through centralized servers. These services are vulnerable to data concentration because all data are sent to a remote server. To solve these problems, we propose self-organizing P2P middleware for healthcare monitoring that enables a real-time multi bio-signal streaming without any central server by connecting the caregiver and care recipient. To verify the performance of the proposed middleware, we evaluated the monitoring service matching time based on a monitoring request. We also confirmed that it is possible to provide an effective monitoring service by evaluating the connectivity between Peer-to-Peer and average jitter.

摘要

随着慢性病老年人口的增加,为他们提供护理的新公共基础设施变得越来越必要。特别是能够实时监测生物信号的技术受到了广泛关注。目前,大多数医疗保健监测服务都是通过无线运营商通过集中式服务器来实现的。这些服务容易受到数据集中的影响,因为所有数据都被发送到远程服务器。为了解决这些问题,我们提出了一种用于医疗保健监测的自组织 P2P 中间件,通过连接护理人员和护理对象,可以在没有任何中央服务器的情况下实现实时多生物信号流。为了验证所提出的中间件的性能,我们根据监测请求评估了监测服务匹配时间。我们还通过评估对等点之间的连接性和平均抖动来确认提供有效监测服务的可能性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/87a1baf33b7c/sensors-17-02650-g022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/713d1b73d8e2/sensors-17-02650-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/7e46eaefb121/sensors-17-02650-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/841ac519b2d1/sensors-17-02650-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/c7a15709575e/sensors-17-02650-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/466c54db0546/sensors-17-02650-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/34b67c6f435b/sensors-17-02650-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/120d7c393fd8/sensors-17-02650-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/e6b6a07a65c3/sensors-17-02650-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/55b56eec2b50/sensors-17-02650-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/dfcde47a82ec/sensors-17-02650-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/d01a13df01ee/sensors-17-02650-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/6a69d4037a72/sensors-17-02650-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/46e97d62777b/sensors-17-02650-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/3e3b44973f65/sensors-17-02650-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/fe4febbeeda3/sensors-17-02650-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/a95626ed15f8/sensors-17-02650-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/84980f044158/sensors-17-02650-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/e5b22d0fd0a1/sensors-17-02650-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/60bbbbc95586/sensors-17-02650-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/951e0b2cadd7/sensors-17-02650-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/c1b524697d0c/sensors-17-02650-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/87a1baf33b7c/sensors-17-02650-g022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/713d1b73d8e2/sensors-17-02650-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/7e46eaefb121/sensors-17-02650-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/841ac519b2d1/sensors-17-02650-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/c7a15709575e/sensors-17-02650-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/466c54db0546/sensors-17-02650-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/34b67c6f435b/sensors-17-02650-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/120d7c393fd8/sensors-17-02650-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/e6b6a07a65c3/sensors-17-02650-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/55b56eec2b50/sensors-17-02650-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/dfcde47a82ec/sensors-17-02650-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/d01a13df01ee/sensors-17-02650-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/6a69d4037a72/sensors-17-02650-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/46e97d62777b/sensors-17-02650-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/3e3b44973f65/sensors-17-02650-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/fe4febbeeda3/sensors-17-02650-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/a95626ed15f8/sensors-17-02650-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/84980f044158/sensors-17-02650-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/e5b22d0fd0a1/sensors-17-02650-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/60bbbbc95586/sensors-17-02650-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/951e0b2cadd7/sensors-17-02650-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/c1b524697d0c/sensors-17-02650-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e3d/5713001/87a1baf33b7c/sensors-17-02650-g022.jpg

相似文献

1
Self-Organizing Peer-To-Peer Middleware for Healthcare Monitoring in Real-Time.面向实时医疗监测的自组织对等中间件。
Sensors (Basel). 2017 Nov 17;17(11):2650. doi: 10.3390/s17112650.
2
An Internet of Things based physiological signal monitoring and receiving system for virtual enhanced health care network.一种用于虚拟增强型医疗保健网络的基于物联网的生理信号监测与接收系统。
Technol Health Care. 2018;26(2):379-385. doi: 10.3233/THC-171173.
3
Towards a flexible middleware for context-aware pervasive and wearable systems.面向上下文感知的普及和可穿戴系统的灵活中间件。
Med Biol Eng Comput. 2012 Nov;50(11):1127-36. doi: 10.1007/s11517-012-0905-9. Epub 2012 Apr 22.
4
A novel middleware solution to improve ubiquitous healthcare systems aided by affective information.一种借助情感信息来改进泛在医疗系统的新型中间件解决方案。
IEEE Trans Inf Technol Biomed. 2010 Mar;14(2):335-49. doi: 10.1109/TITB.2010.2042608.
5
MyHealthAssistant: an event-driven middleware for multiple medical applications on a smartphone-mediated body sensor network.我的健康助手:智能手机介导的体域网中多个医疗应用的事件驱动中间件。
IEEE J Biomed Health Inform. 2015 Mar;19(2):752-60. doi: 10.1109/JBHI.2014.2326604. Epub 2014 May 22.
6
Strategies for P2P connectivity in reconfigurable converged wired/wireless access networks.可重构融合有线/无线接入网络中的对等网络连接策略。
Opt Express. 2010 Dec 6;18(25):26196-205. doi: 10.1364/OE.18.026196.
7
On Providing Multi-Level Quality of Service for Operating Rooms of the Future.为未来手术室提供多层次服务质量。
Sensors (Basel). 2019 May 18;19(10):2303. doi: 10.3390/s19102303.
8
Design of a patient-centered, multi-institutional healthcare information network using peer-to-peer communication in a highly distributed architecture.在高度分布式架构中使用对等通信设计以患者为中心的多机构医疗信息网络。
Stud Health Technol Inform. 2004;107(Pt 2):1048-52.
9
Real-Time Remote Health-Monitoring Systems in a Medical Centre: A Review of the Provision of Healthcare Services-Based Body Sensor Information, Open Challenges and Methodological Aspects.医疗中心的实时远程健康监测系统:基于身体传感器信息的医疗服务提供、开放挑战和方法学方面的综述。
J Med Syst. 2018 Jul 25;42(9):164. doi: 10.1007/s10916-018-1006-6.
10
Sharable EHR systems in Finland.芬兰的可共享电子健康记录系统。
Stud Health Technol Inform. 2006;121:364-70.

本文引用的文献

1
An IoT-Based Computational Framework for Healthcare Monitoring in Mobile Environments.基于物联网的移动环境医疗监测计算框架。
Sensors (Basel). 2017 Oct 10;17(10):2302. doi: 10.3390/s17102302.
2
A Survey on Mobility Support in Wireless Body Area Networks.无线体域网中移动性支持的一项调查。
Sensors (Basel). 2017 Apr 7;17(4):797. doi: 10.3390/s17040797.
3
A Survey on Wireless Body Area Networks for eHealthcare Systems in Residential Environments.针对住宅环境中电子医疗保健系统的无线体域网调查。
Sensors (Basel). 2016 Jun 7;16(6):831. doi: 10.3390/s16060831.
4
Self-organizing distributed architecture supporting dynamic space expanding and reducing in indoor LBS environment.支持室内位置服务环境中动态空间扩展和缩减的自组织分布式架构。
Sensors (Basel). 2015 May 26;15(6):12156-79. doi: 10.3390/s150612156.
5
Fully distributed monitoring architecture supporting multiple trackees and trackers in indoor mobile asset management application.在室内移动资产管理应用中支持多个被跟踪对象和跟踪器的全分布式监测架构。
Sensors (Basel). 2014 Mar 21;14(3):5702-24. doi: 10.3390/s140305702.
6
Security issues in healthcare applications using wireless medical sensor networks: a survey.使用无线医疗传感器网络的医疗应用中的安全问题:调查。
Sensors (Basel). 2012;12(1):55-91. doi: 10.3390/s120100055. Epub 2011 Dec 22.