Yang Zhe, Zhou Qihao, Lei Lei, Zheng Kan, Xiang Wei
Intelligent Computing and Communication (IC2) Lab Key Lab, Key Lab of Universal Wireless Communications, Ministry of Education, Beijing University of Posts & Telecommunications, Beijing, 100088, China.
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China.
J Med Syst. 2016 Dec;40(12):286. doi: 10.1007/s10916-016-0644-9. Epub 2016 Oct 29.
Public healthcare has been paid an increasing attention given the exponential growth human population and medical expenses. It is well known that an effective health monitoring system can detect abnormalities of health conditions in time and make diagnoses according to the gleaned data. As a vital approach to diagnose heart diseases, ECG monitoring is widely studied and applied. However, nearly all existing portable ECG monitoring systems cannot work without a mobile application, which is responsible for data collection and display. In this paper, we propose a new method for ECG monitoring based on Internet-of-Things (IoT) techniques. ECG data are gathered using a wearable monitoring node and are transmitted directly to the IoT cloud using Wi-Fi. Both the HTTP and MQTT protocols are employed in the IoT cloud in order to provide visual and timely ECG data to users. Nearly all smart terminals with a web browser can acquire ECG data conveniently, which has greatly alleviated the cross-platform issue. Experiments are carried out on healthy volunteers in order to verify the reliability of the entire system. Experimental results reveal that the proposed system is reliable in collecting and displaying real-time ECG data, which can aid in the primary diagnosis of certain heart diseases.
鉴于人口和医疗费用的指数级增长，公共医疗保健受到了越来越多的关注。众所周知，有效的健康监测系统可以及时检测健康状况异常，并根据收集到的数据进行诊断。作为诊断心脏病的重要方法，心电图监测得到了广泛研究和应用。然而，几乎所有现有的便携式心电图监测系统都离不开移动应用程序，该应用程序负责数据收集和显示。在本文中，我们提出了一种基于物联网（IoT）技术的心电图监测新方法。心电图数据通过可穿戴监测节点收集，并使用Wi-Fi直接传输到物联网云。物联网云中采用HTTP和MQTT协议，以便向用户提供可视化且及时的心电图数据。几乎所有带有网络浏览器的智能终端都可以方便地获取心电图数据，这大大缓解了跨平台问题。为了验证整个系统的可靠性，对健康志愿者进行了实验。实验结果表明，所提出的系统在收集和显示实时心电图数据方面是可靠的，有助于某些心脏病的初步诊断。
