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Feature level fusion for biometric verification with two-lead ECG signals

Electrocardiogram (ECG) is a new generation of biometric modality which has unique identity properties for human recognition. There are few studies on feature level fusion over short-term ECG signals for extracting non-fiducial features from autocorrelation of ECG windows with an identical length. I...

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Main Authors: Hejazi, Maryamsadat, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Hashim, Shaiful Jahari, Abdul Aziz, Ahmad Fazli, Singh, Yashwant Prasad
Format: Conference or Workshop Item
Language:English
Published: IEEE 2016
Online Access:http://psasir.upm.edu.my/id/eprint/52402/1/Feature%20level%20fusion%20for%20biometric%20verification%20with%20two-lead%20ECG%20signals.pdf
http://psasir.upm.edu.my/id/eprint/52402/
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spelling my.upm.eprints.524022017-06-06T08:28:11Z http://psasir.upm.edu.my/id/eprint/52402/ Feature level fusion for biometric verification with two-lead ECG signals Hejazi, Maryamsadat Syed Mohamed, Syed Abdul Rahman Al-Haddad Hashim, Shaiful Jahari Abdul Aziz, Ahmad Fazli Singh, Yashwant Prasad Electrocardiogram (ECG) is a new generation of biometric modality which has unique identity properties for human recognition. There are few studies on feature level fusion over short-term ECG signals for extracting non-fiducial features from autocorrelation of ECG windows with an identical length. In this paper, we provide an experimental study on fusion at feature extraction level by using autocorrelation method in conjunction with different dimensionality reduction techniques over vector sets with different window lengths from short and long-term two-lead ECG recordings. The results indicate that the window and recording lengths have significant effects on recognition rates of the fused ECG data sets. IEEE 2016 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/52402/1/Feature%20level%20fusion%20for%20biometric%20verification%20with%20two-lead%20ECG%20signals.pdf Hejazi, Maryamsadat and Syed Mohamed, Syed Abdul Rahman Al-Haddad and Hashim, Shaiful Jahari and Abdul Aziz, Ahmad Fazli and Singh, Yashwant Prasad (2016) Feature level fusion for biometric verification with two-lead ECG signals. In: 2016 IEEE 12th IEEE International Colloquium on Signal Processing and its Applications (CSPA2016), 4-6 Mar. 2016, Melaka, Malaysia. (pp. 54-59). 10.1109/CSPA.2016.7515803
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Electrocardiogram (ECG) is a new generation of biometric modality which has unique identity properties for human recognition. There are few studies on feature level fusion over short-term ECG signals for extracting non-fiducial features from autocorrelation of ECG windows with an identical length. In this paper, we provide an experimental study on fusion at feature extraction level by using autocorrelation method in conjunction with different dimensionality reduction techniques over vector sets with different window lengths from short and long-term two-lead ECG recordings. The results indicate that the window and recording lengths have significant effects on recognition rates of the fused ECG data sets.
format Conference or Workshop Item
author Hejazi, Maryamsadat
Syed Mohamed, Syed Abdul Rahman Al-Haddad
Hashim, Shaiful Jahari
Abdul Aziz, Ahmad Fazli
Singh, Yashwant Prasad
spellingShingle Hejazi, Maryamsadat
Syed Mohamed, Syed Abdul Rahman Al-Haddad
Hashim, Shaiful Jahari
Abdul Aziz, Ahmad Fazli
Singh, Yashwant Prasad
Feature level fusion for biometric verification with two-lead ECG signals
author_facet Hejazi, Maryamsadat
Syed Mohamed, Syed Abdul Rahman Al-Haddad
Hashim, Shaiful Jahari
Abdul Aziz, Ahmad Fazli
Singh, Yashwant Prasad
author_sort Hejazi, Maryamsadat
title Feature level fusion for biometric verification with two-lead ECG signals
title_short Feature level fusion for biometric verification with two-lead ECG signals
title_full Feature level fusion for biometric verification with two-lead ECG signals
title_fullStr Feature level fusion for biometric verification with two-lead ECG signals
title_full_unstemmed Feature level fusion for biometric verification with two-lead ECG signals
title_sort feature level fusion for biometric verification with two-lead ecg signals
publisher IEEE
publishDate 2016
url http://psasir.upm.edu.my/id/eprint/52402/1/Feature%20level%20fusion%20for%20biometric%20verification%20with%20two-lead%20ECG%20signals.pdf
http://psasir.upm.edu.my/id/eprint/52402/
_version_ 1643835238843940864
score 13.211869

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