Early predictionof cardiovascular diseases using ECG signal: A review

The 2nd International Malaysia-Ireland Joint Symposium on Engineering, Science and Business 2012 (IMiEJS2012) jointly organized by Universiti Malaysia Perlis and Athlone Institute of Technology in collaboration with The Ministry of Higher Education (MOHE) Malaysia, Education Malaysia and Malaysia Po...

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Main Authors: Nurul Hikmah, Kamaruddin, Murugappan, Muthusamy, Dr., Mohd Iqbal, Omar, Assoc. Prof. Dr.
Other Authors: nurulhikmah88@gmail.com
Format: Working Paper
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2013
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Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/29014
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spelling my.unimap-290142013-10-21T07:07:45Z Early predictionof cardiovascular diseases using ECG signal: A review Nurul Hikmah, Kamaruddin Murugappan, Muthusamy, Dr. Mohd Iqbal, Omar, Assoc. Prof. Dr. nurulhikmah88@gmail.com murugappan@unimap.edu.my iqbalomar@unimap.edu.my Cardiovascular disease (CVD) Myocardial Ischemia Electrocardiogram (ECG) ST segment Discrete Wavelet Transform (DWT) Support Vector Machine (SVM) The 2nd International Malaysia-Ireland Joint Symposium on Engineering, Science and Business 2012 (IMiEJS2012) jointly organized by Universiti Malaysia Perlis and Athlone Institute of Technology in collaboration with The Ministry of Higher Education (MOHE) Malaysia, Education Malaysia and Malaysia Postgraduates Student Association Ireland (MyPSI), 18th - 19th June 2012 at Putra World Trade Center (PWTC), Kuala Lumpur, Malaysia. Electrocardiography is considered a representative signal of cardiac physiology. ECG signal analysis can provide lots of information about heart condition whether it is normal and abnormal. Cardiovascular Disease (CVD) is one of the major leading causes of mortality in the worldwide including Malaysia. The main cardiovascular diseases are heart attack, angina, stroke and peripheral vascular disease (PVD). There are many risk factors that can be major reason for the cause of heart/cardiovascular diseases and also premature death. Recent survey has pointed out that, by 2030, almost 23.6 million people will die from CVDs, mainly from heart disease and stroke. These are projected to remain the single leading causes of death.Most of the other cardiovascular diseases and coronary heart diseases are caused by the progression of atherosclerosis. One of the progressions of atherosclerosis is myocardial ischemia; where this condition is caused by the lack of oxygen and nutrients to the contractile cells [3]. Usually, ischemia is expressed in the ECG signal as ST segment deviations and/or T wave changes [15].These ST segment morphology compatible with ischemia (ischemic changes) usually obtained by recording the ECG signal over long period of time. Ischemia changes of the ECG frequently affect the entire wave shape of ST-T complex, thus are inadequately described by isolated feature such as ST slope, ST-J amplitude and positive and negative amplitude of the T wave. In order to identify the abnormal CVDs due to the traditional risk factor such as tobacco smoking, there are several types of classifier can be used in the previous research works such as Artificial Neural Network (ANN)[21], Fuzzy Logic system[22], Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM). Most of the researchers have used SVM and Fuzzy Logic system for CVDs classification using ECG signals [3] [10] [11][23]. 2013-10-21T07:07:45Z 2013-10-21T07:07:45Z 2012-06-18 Working Paper p. 1124 - 1129 978-967-5760-11-2 http://hdl.handle.net/123456789/29014 en Proceedings of the The 2nd International Malaysia-Ireland Joint Symposium on Engineering, Science and Business 2012 (IMiEJS2012); Universiti Malaysia Perlis (UniMAP)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Cardiovascular disease (CVD)
Myocardial Ischemia
Electrocardiogram (ECG)
ST segment
Discrete Wavelet Transform (DWT)
Support Vector Machine (SVM)
spellingShingle Cardiovascular disease (CVD)
Myocardial Ischemia
Electrocardiogram (ECG)
ST segment
Discrete Wavelet Transform (DWT)
Support Vector Machine (SVM)
Nurul Hikmah, Kamaruddin
Murugappan, Muthusamy, Dr.
Mohd Iqbal, Omar, Assoc. Prof. Dr.
Early predictionof cardiovascular diseases using ECG signal: A review
description The 2nd International Malaysia-Ireland Joint Symposium on Engineering, Science and Business 2012 (IMiEJS2012) jointly organized by Universiti Malaysia Perlis and Athlone Institute of Technology in collaboration with The Ministry of Higher Education (MOHE) Malaysia, Education Malaysia and Malaysia Postgraduates Student Association Ireland (MyPSI), 18th - 19th June 2012 at Putra World Trade Center (PWTC), Kuala Lumpur, Malaysia.
author2 nurulhikmah88@gmail.com
author_facet nurulhikmah88@gmail.com
Nurul Hikmah, Kamaruddin
Murugappan, Muthusamy, Dr.
Mohd Iqbal, Omar, Assoc. Prof. Dr.
format Working Paper
author Nurul Hikmah, Kamaruddin
Murugappan, Muthusamy, Dr.
Mohd Iqbal, Omar, Assoc. Prof. Dr.
author_sort Nurul Hikmah, Kamaruddin
title Early predictionof cardiovascular diseases using ECG signal: A review
title_short Early predictionof cardiovascular diseases using ECG signal: A review
title_full Early predictionof cardiovascular diseases using ECG signal: A review
title_fullStr Early predictionof cardiovascular diseases using ECG signal: A review
title_full_unstemmed Early predictionof cardiovascular diseases using ECG signal: A review
title_sort early predictionof cardiovascular diseases using ecg signal: a review
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2013
url http://dspace.unimap.edu.my/xmlui/handle/123456789/29014
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score 13.160551