Mobile ECG acquisition device for early diagnosis based on Pan-Tompkins algorithm

In recent years, the usage of mobile electrocardiogram (ECG) devices has drawn much attention not only to in house patients but to home patients as well. The devices are truly useful for cardiac patients who need continuous monitoring while they are engaged in daily activities. The portable ECG devi...

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Bibliographic Details
Main Author: Khairuzzaman, Nur Izyan (Author)
Format: Thesis
Published: 2018.
Subjects:
Online Access:Get fulltext
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001 79461
042 |a dc 
100 1 0 |a Khairuzzaman, Nur Izyan  |e author 
245 0 0 |a Mobile ECG acquisition device for early diagnosis based on Pan-Tompkins algorithm 
260 |c 2018. 
520 |a In recent years, the usage of mobile electrocardiogram (ECG) devices has drawn much attention not only to in house patients but to home patients as well. The devices are truly useful for cardiac patients who need continuous monitoring while they are engaged in daily activities. The portable ECG devices particularly facilitate real time ECG recording and analysis for further examination by the doctors. This project focuses on implementing a mobile ECG acquisition device using Arduino UNO, Bluetooth HC-05 and AD8232 Heart Rate Monitor. Pan-Tompkins algorithm is used for QRS complex detection in order to classify the ECG signals either as normal or abnormal that is useful for early diagnosis. The goal of interest is to obtain a correct detection of QRS complex with high accuracy. Thus, the Pan-Tompkins algorithm is suitable as it is a well-known, simple yet efficient method in detecting QRS complexes accurately. The device acquires a Bluetooth technology to send raw data of ECG signal to Android smartphone. The ECG signals are displayed on the mobile interface and then the ECG signal analysis will be carried out by developing the Java-based Android application. The application will offer ECG processing techniques including R-R interval and QRS duration parameter extraction analysis. This device provides three ECG electrodes using Lead II placement for recording. The traces of the ECG leads are then plotted by the app. After that, the ECG data are saved as text files in the phone storage. The users also can view their history records of the previous ECG recording. The mobile app can capture and plot the incoming ECG signals from the remote device. The results shown that for a normal ECG signals, it will have the following parameters; heart rate of 60 to 100 beats per second, R-R interval duration of 0.4s to 1.2s, and QRS duration of 0.06s to 0.10s; else it will considered as abnormal signal. 
546 |a en 
650 0 4 |a TK Electrical engineering. Electronics Nuclear engineering 
655 7 |a Thesis 
787 0 |n http://eprints.utm.my/id/eprint/79461/ 
856 |z Get fulltext  |u http://eprints.utm.my/id/eprint/79461/1/NurIzyanKhairuzzamanMFKE2018.pdf