Simple and efficient multibiometric technique for subject recognition using multilead electrocardiogram signal

In this paper, a simple and effective multibiometric technique for subject recognition using multiple lead electrocardiogram (ECG) signals is presented. The proposed technique significantly improves the recognition performance of a biometric system by using multiple sources available in the same mod...

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Main Authors: Sidek, Khairul Azami, M. Shobaki, Mohammed, Khalil, Ibrahim, Khan, Sheroz, Alam, A. H. M. Zahirul, Abd Malik, Noreha
Format: Proceeding Paper
Language:English
Published: 2013
Subjects:
Online Access:http://irep.iium.edu.my/35233/
http://irep.iium.edu.my/35233/1/icsima2013.pdf
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author Sidek, Khairul Azami
M. Shobaki, Mohammed
Khalil, Ibrahim
Khan, Sheroz
Alam, A. H. M. Zahirul
Abd Malik, Noreha
author_facet Sidek, Khairul Azami
M. Shobaki, Mohammed
Khalil, Ibrahim
Khan, Sheroz
Alam, A. H. M. Zahirul
Abd Malik, Noreha
author_sort Sidek, Khairul Azami
building IIUM Repository
collection Online Access
description In this paper, a simple and effective multibiometric technique for subject recognition using multiple lead electrocardiogram (ECG) signals is presented. The proposed technique significantly improves the recognition performance of a biometric system by using multiple sources available in the same modality group. A total of 30 subjects with 12 lead ECG measurements obtained from PTB Diagnostic ECG database (PTBDB) with sampling rate of 1000 Hz were used to verify the approach. Normalization plays an important role in the identification stage as it uniquely matches between ECG signals from bipolar limb leads and also the supplementary augmented unipolar limb leads. Based on the experimentation results, self-similarities are prominent and distinct from one person to another by obtaining high correlation values and relatively good classification accuracies ranging from 93% to 100% for all the leads. This result also suggests the robustness, reliability and stability of the proposed method for multibiometric system.
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format Proceeding Paper
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institution International Islamic University Malaysia
institution_category Local University
language English
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publishDate 2013
recordtype eprints
repository_type Digital Repository
spelling iium-352332021-01-18T05:13:23Z http://irep.iium.edu.my/35233/ Simple and efficient multibiometric technique for subject recognition using multilead electrocardiogram signal Sidek, Khairul Azami M. Shobaki, Mohammed Khalil, Ibrahim Khan, Sheroz Alam, A. H. M. Zahirul Abd Malik, Noreha TK7885 Computer engineering In this paper, a simple and effective multibiometric technique for subject recognition using multiple lead electrocardiogram (ECG) signals is presented. The proposed technique significantly improves the recognition performance of a biometric system by using multiple sources available in the same modality group. A total of 30 subjects with 12 lead ECG measurements obtained from PTB Diagnostic ECG database (PTBDB) with sampling rate of 1000 Hz were used to verify the approach. Normalization plays an important role in the identification stage as it uniquely matches between ECG signals from bipolar limb leads and also the supplementary augmented unipolar limb leads. Based on the experimentation results, self-similarities are prominent and distinct from one person to another by obtaining high correlation values and relatively good classification accuracies ranging from 93% to 100% for all the leads. This result also suggests the robustness, reliability and stability of the proposed method for multibiometric system. 2013 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/35233/1/icsima2013.pdf Sidek, Khairul Azami and M. Shobaki, Mohammed and Khalil, Ibrahim and Khan, Sheroz and Alam, A. H. M. Zahirul and Abd Malik, Noreha (2013) Simple and efficient multibiometric technique for subject recognition using multilead electrocardiogram signal. In: IEEE International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA), 26-27 Nov 2013, Kuala Lumpur Malaysia. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6717972
spellingShingle TK7885 Computer engineering
Sidek, Khairul Azami
M. Shobaki, Mohammed
Khalil, Ibrahim
Khan, Sheroz
Alam, A. H. M. Zahirul
Abd Malik, Noreha
Simple and efficient multibiometric technique for subject recognition using multilead electrocardiogram signal
title Simple and efficient multibiometric technique for subject recognition using multilead electrocardiogram signal
title_full Simple and efficient multibiometric technique for subject recognition using multilead electrocardiogram signal
title_fullStr Simple and efficient multibiometric technique for subject recognition using multilead electrocardiogram signal
title_full_unstemmed Simple and efficient multibiometric technique for subject recognition using multilead electrocardiogram signal
title_short Simple and efficient multibiometric technique for subject recognition using multilead electrocardiogram signal
title_sort simple and efficient multibiometric technique for subject recognition using multilead electrocardiogram signal
topic TK7885 Computer engineering
url http://irep.iium.edu.my/35233/
http://irep.iium.edu.my/35233/
http://irep.iium.edu.my/35233/1/icsima2013.pdf