An approach to detect QRS complex using backpropagation neural network

Backpropagation Neural Network is used to learn the characteristics of R peak to detect QRS complex. This allows R peak to be differentiated from large peaked T and P waves with higher accuracy and minimizes the problem associated with the noises in the ECG signal includes power line interference, m...

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Bibliographic Details
Main Authors:	Reaz, Mamun Bin Ibne, Ibrahimy, Muhammad Ibn, Ab Rahim, Rosminazuin
Format:	Conference or Workshop Item
Language:	English
Published:	2006
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/36663/ http://irep.iium.edu.my/36663/ http://irep.iium.edu.my/36663/1/c-9_523-116.pdf

id	iium-36663
recordtype	eprints
spelling	iium-366632014-05-21T08:20:38Z http://irep.iium.edu.my/36663/ An approach to detect QRS complex using backpropagation neural network Reaz, Mamun Bin Ibne Ibrahimy, Muhammad Ibn Ab Rahim, Rosminazuin T Technology (General) Backpropagation Neural Network is used to learn the characteristics of R peak to detect QRS complex. This allows R peak to be differentiated from large peaked T and P waves with higher accuracy and minimizes the problem associated with the noises in the ECG signal includes power line interference, motion artifacts, baseline drift, ECG amplitude modulation and other composite noises. The features that trains the network includes amplitude, differentiation value, duration exceed threshold, RR interval and crossing-zero. The performance was tested and resulting in accuracy to detect the correct positive peak was 91.16%. 2006 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/36663/1/c-9_523-116.pdf Reaz, Mamun Bin Ibne and Ibrahimy, Muhammad Ibn and Ab Rahim, Rosminazuin (2006) An approach to detect QRS complex using backpropagation neural network. In: 7th WSEAS International Conference on Neural Networks, 12-14 June, 2006, Cavtat, Croatia. http://www.wseas.us/e-library/conferences/2006cavtat/nn/index.htm
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Reaz, Mamun Bin Ibne Ibrahimy, Muhammad Ibn Ab Rahim, Rosminazuin An approach to detect QRS complex using backpropagation neural network
description	Backpropagation Neural Network is used to learn the characteristics of R peak to detect QRS complex. This allows R peak to be differentiated from large peaked T and P waves with higher accuracy and minimizes the problem associated with the noises in the ECG signal includes power line interference, motion artifacts, baseline drift, ECG amplitude modulation and other composite noises. The features that trains the network includes amplitude, differentiation value, duration exceed threshold, RR interval and crossing-zero. The performance was tested and resulting in accuracy to detect the correct positive peak was 91.16%.
format	Conference or Workshop Item
author	Reaz, Mamun Bin Ibne Ibrahimy, Muhammad Ibn Ab Rahim, Rosminazuin
author_facet	Reaz, Mamun Bin Ibne Ibrahimy, Muhammad Ibn Ab Rahim, Rosminazuin
author_sort	Reaz, Mamun Bin Ibne
title	An approach to detect QRS complex using backpropagation neural network
title_short	An approach to detect QRS complex using backpropagation neural network
title_full	An approach to detect QRS complex using backpropagation neural network
title_fullStr	An approach to detect QRS complex using backpropagation neural network
title_full_unstemmed	An approach to detect QRS complex using backpropagation neural network
title_sort	approach to detect qrs complex using backpropagation neural network
publishDate	2006
url	http://irep.iium.edu.my/36663/ http://irep.iium.edu.my/36663/ http://irep.iium.edu.my/36663/1/c-9_523-116.pdf
first_indexed	2023-09-18T20:52:32Z
last_indexed	2023-09-18T20:52:32Z
_version_	1777410089613787136

An approach to detect QRS complex using backpropagation neural network

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