Wavelet analysis of the ECG signals for three common heart diseases in Jordan
The electrocardiogram is a common diagnostic tool used to monitor heart activity and can provide information about the cardiovascular problems. An automatic detection of the ECG traces can be valuable aid in the diagnosis process. The wavelet transform has proven to be an important tool in the anal...
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iium-217092012-11-07T03:52:05Z http://irep.iium.edu.my/21709/ Wavelet analysis of the ECG signals for three common heart diseases in Jordan Chebil, Jalel Al Nabulsi, Jamal TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices The electrocardiogram is a common diagnostic tool used to monitor heart activity and can provide information about the cardiovascular problems. An automatic detection of the ECG traces can be valuable aid in the diagnosis process. The wavelet transform has proven to be an important tool in the analysis of biomedical signals, and the ECG in particular. This paper proposes a method for the classification of various types of ECG signals using wavelet transform. The method is developed based on the ECG data collected at different local hospitals in Jordan. The data include normal ECG records from healthy people and abnormal ECG signals taken from patients with common heart diseases in Jordan such as right atrial hypertrophy, left atrial hypertrophy and hypocalcaemia IIUM Press 2011 Book Chapter PeerReviewed application/pdf en http://irep.iium.edu.my/21709/1/WAVELET_ANALYSIS_OF_THE_ECG_SIGNALS_FOR_THREE_COMMON_HEART_DISEASES_IN_JORDAN.pdf Chebil, Jalel and Al Nabulsi, Jamal (2011) Wavelet analysis of the ECG signals for three common heart diseases in Jordan. In: Principle of Transducer Devices and Components. IIUM Press, Kuala Lumpur, pp. 291-301. ISBN 978-967-418-172-7 http://rms.research.iium.edu.my/bookstore/default.aspx |
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Digital Repository |
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institution |
International Islamic University Malaysia |
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IIUM Repository |
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Online Access |
language |
English |
topic |
TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices |
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TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices Chebil, Jalel Al Nabulsi, Jamal Wavelet analysis of the ECG signals for three common heart diseases in Jordan |
description |
The electrocardiogram is a common diagnostic tool used to monitor heart activity and can provide information about the cardiovascular problems. An automatic detection of the
ECG traces can be valuable aid in the diagnosis process. The wavelet transform has proven to be an important tool in the analysis of biomedical signals, and the ECG in
particular. This paper proposes a method for the classification of various types of ECG signals using wavelet transform. The method is developed based on the ECG data collected at different local hospitals in Jordan. The data include normal ECG records from healthy people and abnormal ECG signals taken from patients with common heart diseases in Jordan such as right atrial hypertrophy, left atrial hypertrophy and hypocalcaemia |
format |
Book Chapter |
author |
Chebil, Jalel Al Nabulsi, Jamal |
author_facet |
Chebil, Jalel Al Nabulsi, Jamal |
author_sort |
Chebil, Jalel |
title |
Wavelet analysis of the ECG signals for three common heart diseases in Jordan
|
title_short |
Wavelet analysis of the ECG signals for three common heart diseases in Jordan
|
title_full |
Wavelet analysis of the ECG signals for three common heart diseases in Jordan
|
title_fullStr |
Wavelet analysis of the ECG signals for three common heart diseases in Jordan
|
title_full_unstemmed |
Wavelet analysis of the ECG signals for three common heart diseases in Jordan
|
title_sort |
wavelet analysis of the ecg signals for three common heart diseases in jordan |
publisher |
IIUM Press |
publishDate |
2011 |
url |
http://irep.iium.edu.my/21709/ http://irep.iium.edu.my/21709/ http://irep.iium.edu.my/21709/1/WAVELET_ANALYSIS_OF_THE_ECG_SIGNALS_FOR_THREE_COMMON_HEART_DISEASES_IN_JORDAN.pdf |
first_indexed |
2023-09-18T20:33:06Z |
last_indexed |
2023-09-18T20:33:06Z |
_version_ |
1777408867319152640 |