文章基本信息

标题：Internet of things based electrocardiogram monitoring system using machine learning algorithm
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作者：Md.Obaidur Rahaman ; F.M.Javed Mehedi Shamrat ; Mohammod Abul Kashem 等
期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2022
卷号：12
期号：4
页码：3739-3751
DOI：10.11591/ijece.v12i4.pp3739-3751
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：In Bangladesh’s rural regions, almost 30% of the population lives in poverty. Rural residents also have restricted access to nursing and diagnostic services due to obsolete healthcare infrastructure. Consequently, as cardiac failure occurs, they usually fail to call the services and adopt the facilities. The internet of things (IoT) offers a massive advantage in addressing cardiac problems. This study proposed a smart IoT-based electrocardiogram (ECG) monitoring system for heart patients. The system is divided into several parts: ECG sensing network (data acquisition), IoT cloud (data transmission), result analysis (data prediction) and monetization. P, Q, R, S, and T are ECG signal properties fetched, pre-processed, analyzed and predicted to age level for future health management. ECG data are saved in the cloud and accessible via message queuing telemetry transport (MQTT) and hypertext transfer protocol (HTTP) servers. The linear regression method is utilized to determine the impact of electrocardiogram signal characteristics and error rate. The prediction was made to see how much variation there was in PQRST regularity and its sufficiency to be utilized in an ECG monitoring device. Recognizing the quality parameter values, acceptable outcomes are achieved. The proposed system will diminish future medical costs and difficulties for heart patients.
关键词：cardiovascular disease;electrocardiogram monitoring system;internet of things;linear regression;message queuing telemetry transport server