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通过物联网监测技术增强互联健康生态系统:Monit4Healthy系统案例研究

Enhancing Connected Health Ecosystems Through IoT-Enabled Monitoring Technologies: A Case Study of the Monit4Healthy System.

作者信息

Ianculescu Marilena, Constantin Victor-Ștefan, Gușatu Andreea-Maria, Petrache Mihail-Cristian, Mihăescu Alina-Georgiana, Bica Ovidiu, Alexandru Adriana

机构信息

National Institute for Research and Development in Informatics, 011455 Bucharest, Romania.

Faculty of Electrical Engineering, Electronics and Information Technology, Valahia University of Targoviste, 130004 Targoviste, Romania.

出版信息

Sensors (Basel). 2025 Apr 4;25(7):2292. doi: 10.3390/s25072292.

DOI:10.3390/s25072292
PMID:40218804
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11991103/
Abstract

The Monit4Healthy system is an IoT-enabled health monitoring solution designed to address critical challenges in real-time biomedical signal processing, energy efficiency, and data transmission. The system's modular design merges wireless communication components alongside a number of physiological sensors, including galvanic skin response, electromyography, photoplethysmography, and EKG, to allow for the remote gathering and evaluation of health information. In order to decrease network load and enable the quick identification of abnormalities, edge computing is used for real-time signal filtering and feature extraction. Flexible data transmission based on context and available bandwidth is provided through a hybrid communication approach that includes Bluetooth Low Energy and Wi-Fi. Under typical monitoring scenarios, laboratory testing shows reliable wireless connectivity and ongoing battery-powered operation. The Monit4Healthy system is appropriate for scalable deployment in connected health ecosystems and portable health monitoring due to its responsive power management approaches and structured data transmission, which improve the resiliency of the system. The system ensures the reliability of signals whilst lowering latency and data volume in comparison to conventional cloud-only systems. Limitations include the requirement for energy profiling, distinctive hardware miniaturizing, and sustained real-world validation. By integrating context-aware processing, flexible design, and effective communication, the Monit4Healthy system complements existing IoT health solutions and promotes better integration in clinical and smart city healthcare environments.

摘要

Monit4Healthy系统是一种支持物联网的健康监测解决方案,旨在应对实时生物医学信号处理、能源效率和数据传输方面的严峻挑战。该系统的模块化设计将无线通信组件与多种生理传感器(包括皮肤电反应、肌电图、光电容积描记法和心电图)相结合,以实现健康信息的远程收集和评估。为了减少网络负载并能快速识别异常情况,边缘计算用于实时信号过滤和特征提取。通过包括低功耗蓝牙和Wi-Fi的混合通信方法,提供基于上下文和可用带宽的灵活数据传输。在典型的监测场景下,实验室测试显示出可靠的无线连接和持续的电池供电运行。由于其响应式电源管理方法和结构化数据传输提高了系统的弹性,Monit4Healthy系统适用于在互联健康生态系统中进行可扩展部署和便携式健康监测。与传统的仅依赖云的系统相比,该系统在确保信号可靠性的同时降低了延迟和数据量。局限性包括对能源分析的要求、独特的硬件小型化以及持续的实际验证。通过集成上下文感知处理、灵活设计和有效通信,Monit4Healthy系统补充了现有的物联网健康解决方案,并促进了在临床和智慧城市医疗环境中的更好集成。

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2
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Sensors (Basel). 2025 Feb 7;25(4):996. doi: 10.3390/s25040996.
3
Designing a Hybrid Energy-Efficient Harvesting System for Head- or Wrist-Worn Healthcare Wearable Devices.为头戴式或腕戴式医疗保健可穿戴设备设计混合节能采集系统。
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4
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Sensors (Basel). 2024 Jun 28;24(13):4201. doi: 10.3390/s24134201.
5
Design and Evaluation of a Low-Power Wide-Area Network (LPWAN)-Based Emergency Response System for Individuals with Special Needs in Smart Buildings.基于低功耗广域网 (LPWAN) 的智能建筑中特殊需求人群应急响应系统的设计与评估。
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6
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Sensors (Basel). 2024 Apr 19;24(8):2607. doi: 10.3390/s24082607.
7
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Int J Med Inform. 2024 May;185:105385. doi: 10.1016/j.ijmedinf.2024.105385. Epub 2024 Feb 24.
8
Benefits and barriers associated with the use of smart home health technologies in the care of older persons: a systematic review.智能家居健康技术在老年人护理中的应用的益处和障碍:系统评价。
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9
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Int J Neural Syst. 2023 Nov;33(11):2350058. doi: 10.1142/S0129065723500582. Epub 2023 Sep 30.
10
Bluetooth-Based Healthcare Information and Medical Resource Management System.基于蓝牙的医疗保健信息和医疗资源管理系统。
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