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IJSTR >> Volume 9 - Issue 6, June 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

An Advanced Embedded System Based Diagnostic Technique For Coronary Artery Disease (CAD) Using Insightful Assessment Of Electrocardiogram With Internet Of Things (IoT)

[Full Text]



M Abdul Wahab Johny, V Violetjuli, L Jayanthi, E Murugan



: Atrioventricular Block (AVB), Coronary Arterial Disease, Graphic User Interface, IoT, MQTT mosquito, Raspberry Pi 3, SoC;



Coronary Arterial Disease (CAD) is the most commonly known heart disease and this disease is one of the prevalent reasons for the high mortality rate. The most obvious way of analysing the different types of heart block is still done on the basis of the graphical assessment of the Electrocardiogram (ECG) graph. Using an analog graph plotted on the existing ECG machine, it is very difficult to perform system-based analysis without live digital data. In this research paper, an instrument was designed for live ECG monitoring in order to create a database for different types of blockage in the heart. Different kinds of an atrioventricular block (AVB) are determined with the aid of ECG graphs delay. So, all such possible cases are determined using a newly developed CAD algorithm for feature extraction, event detection and temporal localization using free open source software Scilab. This paper has also proposed a novel method for consistently monitoring the heart block with the help of MQTT using the Internet of Things. The data retrieved from the ECG graph is collected via the sensor (AD8232) developed by Texas Instruments and known for its high sensitivity. Further, the data are transmitted through 16-bit analog to digital converter (ADS1115) and by using I2C protocol, it is interfaced with Raspberry Pi 3. With the support of IEEE 802.11 (WLAN) and an in-built Raspberry Pi 3 module, MQTT mosquito client was developed which publishes the data received by the ADC to Cloud MQTT. The main purpose of using the MQTT subscribe is to accurately assess the ECG data for detecting the delay and finally correlating with the specific type of heart block and finally using Graphic User Interface (GUI) yet another advantage is that the data can be remotely assessed from any part of the world.



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