Machine and Deep Learning Techniques, Body Sensor Networks, and Internet of Things-based Smart Healthcare Systems in COVID-19 Remote Patient Monitoring

Diana Michalkova Lucia Machova Veronika Stone
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引用次数: 5

Abstract

Keywords: remote patient monitoring;body sensor network;COVID-19 1.Introduction The purpose of our systematic review is to examine the recently published literature on COVID-19 remote patient monitoring and integrate the insights it configures on machine and deep learning techniques, body sensor networks, and Internet of Things-based smart healthcare systems. The manuscript is organized as following: theoretical overview (section 2), methodology (section 3), COVID-19 physiological sensor data measurement and healthcare monitoring (section 4), COVID-19 detection and monitoring tools (section 5), Internet of Medical Things-enabled remote healthcare services (section 6), discussion (section 7), synopsis of the main research outcomes (section 8), conclusions (section 9), limitations, implications, and further directions of research (section 10). Internet of Things-enabled wearable medical devices and biological sensors transfer relevant data to optimize the performance of medical personnel, integrating monitoring and prevention, and treatment strategies. Medical data exchange can result in enhanced healthcare quality and systems, optimizing the feedback time in emergency situations, and precise detection and control of COVID-19.
机器和深度学习技术、身体传感器网络和基于物联网的智能医疗保健系统在COVID-19远程患者监测中的应用
关键词:患者远程监护;身体传感器网络;COVID-19我们系统综述的目的是研究最近发表的关于COVID-19远程患者监测的文献,并整合其对机器和深度学习技术、身体传感器网络和基于物联网的智能医疗系统的见解。该论文组织如下:理论概述(第2节)、方法(第3节)、COVID-19生理传感器数据测量和医疗监测(第4节)、COVID-19检测和监测工具(第5节)、基于医疗物联网的远程医疗服务(第6节)、讨论(第7节)、主要研究成果概述(第8节)、结论(第9节)、局限性、影响和进一步的研究方向(第10节)。基于物联网的可穿戴医疗设备和生物传感器传输相关数据,优化医务人员的绩效,整合监测、预防和治疗策略。医疗数据交换可以提高医疗质量和系统,优化紧急情况下的反馈时间,并精确检测和控制COVID-19。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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