基于物联网的智能医疗系统和无线生物医学传感设备在COVID-19监测、检测和预防中的应用

Anna Riley
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引用次数: 13

摘要

在数据处理和存储(Andronie等人,2021a, b)中利用云和无线传感器网络(l等人,2021)可以通过分析健康状况和行为变化来确保监测康复和恢复过程。研究设计、调查方法和材料访谈是在线进行的,数据采用人口普查局美国社区调查的五个变量(年龄、种族/民族、性别、教育程度和地理区域)加权,以可靠和准确地反映美国的人口构成。利用生物医学大数据分析、云计算和基于机器学习的实时数据传感和处理的智能和计算机化分子诊断工具的进步(Kovacova和l z roiu, 2021)可以协助COVID-19的检测、监测和治疗,并为支持性决策提供云数据存储。在2019冠状病毒病大流行期间,医疗物联网通过使用无线生物医学传感设备,协助智能医疗系统分析收集的数据,集成可穿戴健康监测传感器、诊断工具和远程医疗设备。
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Internet of Things-based Smart Healthcare Systems and Wireless Biomedical Sensing Devices in Monitoring, Detection, and Prevention of COVID-19
(Usak et al., 2020) Cloud and wireless sensor networks (Lăzăroiu et al., 2021) harnessed in data processing and storage (Andronie et al., 2021a, b) can ensure monitoring rehabilitation and recovery processes by analyzing health status and behavioral changes. Study Design, Survey Methods, and Materials The interviews were conducted online and data were weighted by five variables (age, race/ethnicity, gender, education, and geographic region) using the Census Bureau's American Community Survey to reflect reliably and accurately the demographic composition of the United States. (Khan and Algarni, 2020) The advancement of smart and computerized molecular diagnostic tools harnessing biomedical big data analysis, cloud computing, and machine learning-based real-time data sensing and processing (Kovacova and Lăzăroiu, 2021) can assist in COVID-19 detection, monitoring, and treatment, and cloud data storage for supportive decisions. Conclusions, Implications, Limitations, and Further Research Directions Internet of Medical Things assists smart healthcare systems in analyzing gathered data, integrating wearable health monitoring sensors, diagnostics tools, and telemedicine equipment during the COVID-19 pandemic by use of wireless biomedical sensing devices.
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