Identification of cardiac autonomic neuropathy patients using cardioid based graph for ECG biometric

In this paper, the application of data mining applied on Cardioid based person identification mechanism using electrocardiogram (ECG) is presented. A total of 50 subjects with Cardiac Autonomic Neuropathy (CAN) were obtained from participants with diabetes from the Charles Sturt Diabetes Complicatio...

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Main Authors:	Sidek, Khairul Azami, Jelinek, Herbert, Khalil, Ibrahim
Format:	Article
Language:	English
Published:	Computing in Cardiology 2011
Subjects:	TK7885 Computer engineering
Online Access:	http://irep.iium.edu.my/31996/ http://irep.iium.edu.my/31996/ http://irep.iium.edu.my/31996/1/cinc2011b.pdf

id	iium-31996
recordtype	eprints
spelling	iium-319962013-09-17T01:35:29Z http://irep.iium.edu.my/31996/ Identification of cardiac autonomic neuropathy patients using cardioid based graph for ECG biometric Sidek, Khairul Azami Jelinek, Herbert Khalil, Ibrahim TK7885 Computer engineering In this paper, the application of data mining applied on Cardioid based person identification mechanism using electrocardiogram (ECG) is presented. A total of 50 subjects with Cardiac Autonomic Neuropathy (CAN) were obtained from participants with diabetes from the Charles Sturt Diabetes Complication Screening Initiative (DiScRi). The patients can be categorized into two types of CAN which are early CAN and definite/severe CAN. Euclidean distances obtained as a result of the formation of the Cardioid based graph were used as extracted features. These distances were then applied in Multilayer Perceptron to confirm the identity of individuals. Our experimentation results suggest that person identification is possible by obtaining classification accuracies of 99.6% for patients with early CAN, 99.1% for patients with severe/definite CAN and 99.3% for all the CAN patients. These results indicate that ECG biometric is possible and QRS complex is not severely affected by CAN with the ability to identify and differentiate individuals. Computing in Cardiology 2011-09-18 Article PeerReviewed application/pdf en http://irep.iium.edu.my/31996/1/cinc2011b.pdf Sidek, Khairul Azami and Jelinek, Herbert and Khalil, Ibrahim (2011) Identification of cardiac autonomic neuropathy patients using cardioid based graph for ECG biometric. Computing in Cardiology, 38. pp. 517-520. ISSN 0276-6574 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6164616
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	TK7885 Computer engineering
spellingShingle	TK7885 Computer engineering Sidek, Khairul Azami Jelinek, Herbert Khalil, Ibrahim Identification of cardiac autonomic neuropathy patients using cardioid based graph for ECG biometric
description	In this paper, the application of data mining applied on Cardioid based person identification mechanism using electrocardiogram (ECG) is presented. A total of 50 subjects with Cardiac Autonomic Neuropathy (CAN) were obtained from participants with diabetes from the Charles Sturt Diabetes Complication Screening Initiative (DiScRi). The patients can be categorized into two types of CAN which are early CAN and definite/severe CAN. Euclidean distances obtained as a result of the formation of the Cardioid based graph were used as extracted features. These distances were then applied in Multilayer Perceptron to confirm the identity of individuals. Our experimentation results suggest that person identification is possible by obtaining classification accuracies of 99.6% for patients with early CAN, 99.1% for patients with severe/definite CAN and 99.3% for all the CAN patients. These results indicate that ECG biometric is possible and QRS complex is not severely affected by CAN with the ability to identify and differentiate individuals.
format	Article
author	Sidek, Khairul Azami Jelinek, Herbert Khalil, Ibrahim
author_facet	Sidek, Khairul Azami Jelinek, Herbert Khalil, Ibrahim
author_sort	Sidek, Khairul Azami
title	Identification of cardiac autonomic neuropathy patients using cardioid based graph for ECG biometric
title_short	Identification of cardiac autonomic neuropathy patients using cardioid based graph for ECG biometric
title_full	Identification of cardiac autonomic neuropathy patients using cardioid based graph for ECG biometric
title_fullStr	Identification of cardiac autonomic neuropathy patients using cardioid based graph for ECG biometric
title_full_unstemmed	Identification of cardiac autonomic neuropathy patients using cardioid based graph for ECG biometric
title_sort	identification of cardiac autonomic neuropathy patients using cardioid based graph for ecg biometric
publisher	Computing in Cardiology
publishDate	2011
url	http://irep.iium.edu.my/31996/ http://irep.iium.edu.my/31996/ http://irep.iium.edu.my/31996/1/cinc2011b.pdf
first_indexed	2023-09-18T20:46:10Z
last_indexed	2023-09-18T20:46:10Z
_version_	1777409689026297856

Identification of cardiac autonomic neuropathy patients using cardioid based graph for ECG biometric

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