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基于物联网的用户跟踪解决方案的系统评价:迈向更智能的生活方式、健康管理和养生。

Systematic Review of IoT-Based Solutions for User Tracking: Towards Smarter Lifestyle, Wellness and Health Management.

机构信息

Faculty of Engineering, Department of Electrical and Computer Engineering, McGill University, Montreal, QC H3A 0G4, Canada.

出版信息

Sensors (Basel). 2024 Sep 13;24(18):5939. doi: 10.3390/s24185939.

Abstract

The Internet of Things (IoT) base has grown to over 20 billion devices currently operational worldwide. As they greatly extend the applicability and use of biosensors, IoT developments are transformative. Recent studies show that IoT, coupled with advanced communication frameworks, such as machine-to-machine (M2M) interactions, can lead to (1) improved efficiency in data exchange, (2) accurate and timely health monitoring, and (3) enhanced user engagement and compliance through advancements in human-computer interaction. This systematic review of the 19 most relevant studies examines the potential of IoT in health and lifestyle management by conducting detailed analyses and quality assessments of each study. Findings indicate that IoT-based systems effectively monitor various health parameters using biosensors, facilitate real-time feedback, and support personalized health recommendations. Key limitations include small sample sizes, insufficient security measures, practical issues with wearable sensors, and reliance on internet connectivity in areas with poor network infrastructure. The reviewed studies demonstrated innovative applications of IoT, focusing on M2M interactions, edge devices, multimodality health monitoring, intelligent decision-making, and automated health management systems. These insights offer valuable recommendations for optimizing IoT technologies in health and wellness management.

摘要

物联网(IoT)基础目前已扩展到全球 200 多亿台设备。由于物联网极大地扩展了生物传感器的适用性和使用范围,因此其发展具有变革性。最近的研究表明,物联网与先进的通信框架(如机器对机器(M2M)交互)相结合,可以实现(1)数据交换效率的提高,(2)准确和及时的健康监测,以及(3)通过人机交互的进步提高用户参与度和合规性。本研究对 19 项最相关研究进行了系统性回顾,通过对每项研究进行详细分析和质量评估,考察了物联网在健康和生活方式管理中的潜力。研究结果表明,基于物联网的系统可以有效地使用生物传感器监测各种健康参数,提供实时反馈,并支持个性化的健康建议。主要限制包括样本量小、安全措施不足、可穿戴传感器的实际问题以及在网络基础设施较差的地区对互联网连接的依赖。综述的研究展示了物联网的创新应用,重点关注 M2M 交互、边缘设备、多模态健康监测、智能决策和自动化健康管理系统。这些见解为优化物联网技术在健康和健康管理中的应用提供了有价值的建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fa84/11435569/c06d55883742/sensors-24-05939-g001.jpg

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