医疗保健与医疗物联网:应用、趋势、主要挑战和拟议解决方案

Inas Al Khatib, A. Shamayleh, Malick Ndiaye
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摘要

近年来,医疗物联网(IoMT)已成为医疗保健领域的一项重大技术进步。本系统综述旨在通过对现有文献的全面分析,确定并总结该领域的各种应用、关键挑战和建议的技术解决方案。本综述重点介绍了 IoMT 的各种应用,包括移动医疗(mHealth)应用、远程生物标记检测、用于手术室擦洗分布的 RFID-IoT 混合解决方案、利用机器学习进行基于 IoT 的疾病预测,以及通过可搜索对称加密、区块链和 IPFS 高效共享个人健康记录。其他值得注意的应用包括远程医疗保健管理系统、无创实时血糖测量设备、分布式账本技术(DLT)平台、超宽带(UWB)雷达系统、基于物联网的脉搏血氧仪、事故与急救信息学(A&EI)以及集成式可穿戴智能贴片。确定的主要挑战包括隐私保护、可持续电源、传感器智能、人类对传感器的适应性、数据速度、设备可靠性和存储效率。建议的缓解措施包括网络控制、密码学、边缘雾计算和区块链,以及严格的风险规划。综述还确定了 IoMT 架构、远程监控创新、机器学习和人工智能的整合以及增强型安全措施的趋势和进展。与现有文献相比,本综述做出了一些新贡献,包括:(1)对 IoMT 应用进行了全面分类,从传统用例扩展到 UWB 雷达系统和 DLT 平台等新兴技术;(2)深入分析了机器学习和人工智能在 IoMT 中的整合,重点介绍了疾病预测和远程监控方面的创新方法;(3) 详细研究隐私和安全措施,提出先进的加密解决方案和区块链实施方案,以加强数据保护;以及 (4) 确定未来的研究方向,为解决当前的局限性和推进对医疗保健领域物联网技术的科学理解提供路线图。通过解决当前的局限性并提出未来的研究方向,这项工作旨在推进对医疗保健领域物联网技术的科学理解。
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Healthcare and the Internet of Medical Things: Applications, Trends, Key Challenges, and Proposed Resolutions
In recent years, the Internet of medical things (IoMT) has become a significant technological advancement in the healthcare sector. This systematic review aims to identify and summarize the various applications, key challenges, and proposed technical solutions within this domain, based on a comprehensive analysis of the existing literature. This review highlights diverse applications of the IoMT, including mobile health (mHealth) applications, remote biomarker detection, hybrid RFID-IoT solutions for scrub distribution in operating rooms, IoT-based disease prediction using machine learning, and the efficient sharing of personal health records through searchable symmetric encryption, blockchain, and IPFS. Other notable applications include remote healthcare management systems, non-invasive real-time blood glucose measurement devices, distributed ledger technology (DLT) platforms, ultra-wideband (UWB) radar systems, IoT-based pulse oximeters, accident and emergency informatics (A&EI), and integrated wearable smart patches. The key challenges identified include privacy protection, sustainable power sources, sensor intelligence, human adaptation to sensors, data speed, device reliability, and storage efficiency. The proposed mitigations encompass network control, cryptography, edge-fog computing, and blockchain, alongside rigorous risk planning. The review also identifies trends and advancements in the IoMT architecture, remote monitoring innovations, the integration of machine learning and AI, and enhanced security measures. This review makes several novel contributions compared to the existing literature, including (1) a comprehensive categorization of IoMT applications, extending beyond the traditional use cases to include emerging technologies such as UWB radar systems and DLT platforms; (2) an in-depth analysis of the integration of machine learning and AI in IoMT, highlighting innovative approaches in disease prediction and remote monitoring; (3) a detailed examination of privacy and security measures, proposing advanced cryptographic solutions and blockchain implementations to enhance data protection; and (4) the identification of future research directions, providing a roadmap for addressing current limitations and advancing the scientific understanding of IoMT in healthcare. By addressing current limitations and suggesting future research directions, this work aims to advance scientific understanding of the IoMT in healthcare.
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