...
首页> 外文期刊>Computer networks >Cloud-assisted Industrial Internet of Things (IIoT) - Enabled framework for health monitoring
【24h】

Cloud-assisted Industrial Internet of Things (IIoT) - Enabled framework for health monitoring

机译:云辅助工业物联网(IIoT)-启用的健康监控框架

获取原文
获取原文并翻译 | 示例
           

摘要

The promising potential of the emerging Internet of Things (IoT) technologies for interconnected medical devices and sensors has played an important role in the next-generation healthcare industry for quality patient care. Because of the increasing number of elderly and disabled people, there is an urgent need for a real-time health monitoring infrastructure for analyzing patients' healthcare data to avoid preventable deaths. Healthcare Industrial IoT (HealthIIoT) has significant potential for the realization of such monitoring. HealthIIoT is a combination of communication technologies, interconnected apps, Things (devices and sensors), and people that would function together as one smart system to monitor, track, and store patients' healthcare information for ongoing care. This paper presents a HealthIIoT-enabled monitoring framework, where ECG and other healthcare data are collected by mobile devices and sensors and securely sent to the cloud for seamless access by healthcare professionals. Signal enhancement, watermarking, and other related analytics will be used to avoid identity theft or clinical error by healthcare professionals. The suitability of this approach has been validated through both experimental evaluation, and simulation by deploying an IoT-driven ECG-based health monitoring service in the cloud. (C) 2016 Elsevier B.V. All rights reserved.
机译:用于互连医疗设备和传感器的新兴物联网(IoT)技术的潜力巨大,在下一代医疗保健行业中为高质量的患者护理发挥了重要作用。由于老年人和残疾人的数量不断增加,因此迫切需要一种实时健康监控基础结构,以分析患者的医疗保健数据,从而避免可预防的死亡。医疗保健工业物联网(HealthIIoT)具有实现此类监控的巨大潜力。 HealthIIoT是通信技术,互连的应用程序,事物(设备和传感器)以及人们的结合体,它们将作为一个智能系统一起运行,以监视,跟踪和存储患者的医疗保健信息以进行持续护理。本文提出了一种支持HealthIIoT的监控框架,其中ECG和其他医疗数据通过移动设备和传感器收集,并安全地发送到云中,以供医疗专业人员无缝访问。信号增强,水印和其他相关分析将被用于避免医疗保健专业人员的身份盗用或临床错误。通过在云中部署IoT驱动的基于ECG的健康监控服务,通过实验评估和仿真都验证了此方法的适用性。 (C)2016 Elsevier B.V.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号