Krishna Charu, Kumar Dinesh, Kushwaha Dharmender Singh
Department of Computer Science & Engineering, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, UP 211004 India.
Department of Computer Science & Engineering, National Institute of Technology Jamshedpur, Jamshedpur, Jharkhand 831014 India.
Wirel Pers Commun. 2023 Jun 2:1-48. doi: 10.1007/s11277-023-10535-9.
Sporadic occurrences of transmissible diseases have severe and long-lasting effects on humankind throughout history. These outbreaks have molded the political, economic, and social aspects of human life. Pandemics have redefined some of the basic beliefs of modern healthcare, pushing researchers and scientists to develop innovative solutions to be better equipped for future emergencies. Numerous attempts have been made to fight Covid-19-like pandemics using technologies such as the Internet of Things, wireless body area network, blockchain, and machine learning. Since the disease is highly contagious, novel research in patients' health monitoring system is essential for the constant monitoring of pandemic patients with minimal or no human intervention. With the ongoing pandemic of SARS-CoV-2, popularly known as Covid-19, innovations for monitoring of patients' vitals and storing them securely have risen more than ever. Analyzing the stored patients' data can further assist healthcare workers in their decision-making process. In this paper, we surveyed the research works on remote monitoring of pandemic patients admitted in hospitals or quarantined at home. First, an overview of pandemic patient monitoring is given followed by a brief introduction of enabling technologies i.e. Internet of Things, blockchain, and machine learning to implement the system. The reviewed works have been classified into three categories; remote monitoring of pandemic patients using IoT, blockchain-based storage or sharing platforms for patients' data, and processing/analyzing the stored patients' data using machine learning for prognosis and diagnosis. We also identified several open research issues to set directions for future research.
在历史上，传染性疾病的零星爆发对人类产生了严重且持久的影响。这些疫情塑造了人类生活的政治、经济和社会层面。大流行重新定义了现代医疗保健的一些基本信念，促使研究人员和科学家开发创新解决方案，以便更好地应对未来的紧急情况。人们已经进行了许多尝试，利用物联网、无线体域网、区块链和机器学习等技术来对抗类似新冠疫情的大流行。由于这种疾病具有高度传染性，因此对患者健康监测系统进行新颖的研究对于在最少或无人干预的情况下持续监测大流行患者至关重要。随着目前被称为新冠疫情的严重急性呼吸综合征冠状病毒2（SARS-CoV-2）大流行的持续，用于监测患者生命体征并安全存储这些数据的创新比以往任何时候都更加突出。分析存储的患者数据可以进一步帮助医护人员进行决策。在本文中，我们调查了关于对住院或居家隔离的大流行患者进行远程监测的研究工作。首先，给出了大流行患者监测的概述，随后简要介绍了实现该系统的使能技术，即物联网、区块链和机器学习。所审查的工作被分为三类：使用物联网对大流行患者进行远程监测、基于区块链的患者数据存储或共享平台，以及使用机器学习对存储的患者数据进行处理/分析以进行预后和诊断。我们还确定了几个开放的研究问题，为未来的研究指明方向。
