Development of Electrocardiograph Monitoring System

Author:

Rosli Khairul Affendi,Omar Mohd. Hafizi,Hasan Ahmad Fariz,Musa Khairil Syahmi,Fadzil Mohd Fairuz Muhamad,Neu Shu Hwei

Abstract

Electrocardiograph (ECG) monitoring system is one of the diagnostic tools which can help in reduce the risk of heart attack. A cardiologist may be able to determine heart condition from the ECG signal that recorded from subject. The purpose was to design an ECG monitoring system which consists of ECG circuit and digital signal processing system to deny the unwanted signal. In general, the ECG signal is nature weak and only around 1mV amplitude. Therefore filter and amplifier circuits were designed into 3 stages with a total gain of 1000 to bring the signal to around 1V. Circuit designed included of instrumentation amplifier, bandpass filter and notch filter. The frequency bandwidth of ECG is between 0.05Hz until 100Hz. Schematic circuit was tested by software simulation before proceeding to hardware implementation. Simulation analysis was done by using Software Proteus 8 Professional while the further signal processing was done in MATLAB software environment. A PQRST ECG waveform can be seen clearly after digital filtering stage in MATLAB environment. Digital signal processing in MATLAB software included of pre-filtering, Fast Fourier transform and peak detection. As conclusion, the time interval between peaks can be determined automatically which can provide useful information in clinical aspect.

Publisher

EDP Sciences

Subject

General Medicine

Reference10 articles.

1. “ECG timeline - History of the electrocardiogram”, Ecglibrary.com, 2016. [Online]. Available: http://www.ecglibrary.com/ecghist.html. [Accessed: 10-May-2016].

2. “Cardiovascular Lab: Electrocardiogram: Setup”, Medicine.mcgill.ca, 2016. [Online]. Available: http://www.medicine.mcgill.ca/physio/vlab/cardio/setup.htm. [Accessed: 10-May-2016].

3. “Adaptive Noise Removal of ECG Signal Based On Ensemble Empirical Mode Decomposition”, 2016. [Online].Available:applications/adaptive-noise-removal-of-ecg-signal-based-on-ensemble-empirical-mode-decomposition. [Accessed: 8-June-2016].

4. PCbasedpatientmonitoringsystem, DevelopmentofECGamplifier”,Library.utem.edu.my, 2016. [Online]. Available:http://library.utem.edu.my/index2.php?option=com_docman&task=doc_view&gid=817&Ite mid=208.[Accessed: 10-Apr-2016].

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Biodegradable Polymer Composites for Electrophysiological Signal Sensing;Polymers;2022-07-15

2. Multiclass Heartbeat Classification using ECG Signals and Convolutional Neural Networks;2022 2nd International Conference on Digital Futures and Transformative Technologies (ICoDT2);2022-05-24

3. Simulation of Abnormal Physiological Signals in a Phantom for Bioengineering Education;International Journal of Online and Biomedical Engineering (iJOE);2020-11-30

4. A portable electrocardiogram for real-time monitoring of cardiac signals;SN Applied Sciences;2020-07-25

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3