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...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2016
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| Online Access: | http://psasir.upm.edu.my/id/eprint/52402/1/Feature%20level%20fusion%20for%20biometric%20verification%20with%20two-lead%20ECG%20signals.pdf |
| _version_ | 1825930718409129984 |
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| author | Hejazi, Maryamsadat Syed Mohamed, Syed Abdul Rahman Al-Haddad Hashim, Shaiful Jahari Abdul Aziz, Ahmad Fazli Singh, Yashwant Prasad |
| 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 |
| collection | UPM |
| 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. |
| first_indexed | 2024-03-06T09:15:49Z |
| format | Conference or Workshop Item |
| id | upm.eprints-52402 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T09:15:49Z |
| publishDate | 2016 |
| publisher | IEEE |
| record_format | dspace |
| spelling | 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 |
| 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 |
| title | 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_short | Feature level fusion for biometric verification with two-lead ECG signals |
| title_sort | feature level fusion for biometric verification with two lead ecg signals |
| url | http://psasir.upm.edu.my/id/eprint/52402/1/Feature%20level%20fusion%20for%20biometric%20verification%20with%20two-lead%20ECG%20signals.pdf |
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