Photoplethysmogram based biometric identification incorporating different age and gender group

Biometric is the authentication and identification of a person by measuring or estimating their physiological characteristics. First generation biometric such as fingerprint, signature and voice have drawback and easily can be duplicated which lead to serious identity theft crime. Therefore, second...

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Main Authors: Azam, Siti Nurfarah Ain, Sidek, Khairul Azami, Ismail, Ahmad Fadzil
Format: Article
Language:English
English
Published: Faculty of Electronic and Computer Engineering (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM) 2018
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Online Access:http://irep.iium.edu.my/63236/7/63236%20%20Photoplethysmogram%20based%20biometric%20identification%20incorporating%20different%20age%20and%20gender%20group%20SCOPUS.pdf
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http://journal.utem.edu.my/index.php/jtec/article/view/3639/2634
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Institution: Universiti Islam Antarabangsa Malaysia
Language: English
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spelling my.iium.irep.632362018-08-09T04:54:34Z http://irep.iium.edu.my/63236/ Photoplethysmogram based biometric identification incorporating different age and gender group Azam, Siti Nurfarah Ain Sidek, Khairul Azami Ismail, Ahmad Fadzil TK7885 Computer engineering Biometric is the authentication and identification of a person by measuring or estimating their physiological characteristics. First generation biometric such as fingerprint, signature and voice have drawback and easily can be duplicated which lead to serious identity theft crime. Therefore, second generation of biometric was introduced by using bio-signal. This study evaluates the possibility of applying PPG as biometric identification system incorporating different age, gender group, and time variability. A total of 36 subjects were involved in this study consists of 18 males and 18 females for age difference and gender analysis. The PPG signals were taken in resting state by using pulse oximeter. The PPG signal was differentiated twice in order to form APG signal. These signals then undergo pre-processing and the segmentation process was done by using MATLAB. The highest peaks from the signal was used as reference point to determine the appropriate distance for one cycle of both signal. Then, the signals were classified by four commonly used classifiers which are Bayes Network, Naïve Bayes, Multilayer Perceptron, and Radial Basis Function. The outcome from this study suggested the accuracy up to 100% for different age group, 91.11% for female subjects and 95% for male subjects. Faculty of Electronic and Computer Engineering (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM) 2018 Article PeerReviewed application/pdf en http://irep.iium.edu.my/63236/7/63236%20%20Photoplethysmogram%20based%20biometric%20identification%20incorporating%20different%20age%20and%20gender%20group%20SCOPUS.pdf application/pdf en http://irep.iium.edu.my/63236/13/63236%20%20Photoplethysmogram%20based%20biometric%20identification%20incorporating%20different%20age%20and%20gender%20group_article.pdf Azam, Siti Nurfarah Ain and Sidek, Khairul Azami and Ismail, Ahmad Fadzil (2018) Photoplethysmogram based biometric identification incorporating different age and gender group. Journal of Telecommunication, Electronic and Computer Engineering, 10 (1-5). pp. 101-108. ISSN 2180-1843 http://journal.utem.edu.my/index.php/jtec/article/view/3639/2634
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic TK7885 Computer engineering
spellingShingle TK7885 Computer engineering
Azam, Siti Nurfarah Ain
Sidek, Khairul Azami
Ismail, Ahmad Fadzil
Photoplethysmogram based biometric identification incorporating different age and gender group
description Biometric is the authentication and identification of a person by measuring or estimating their physiological characteristics. First generation biometric such as fingerprint, signature and voice have drawback and easily can be duplicated which lead to serious identity theft crime. Therefore, second generation of biometric was introduced by using bio-signal. This study evaluates the possibility of applying PPG as biometric identification system incorporating different age, gender group, and time variability. A total of 36 subjects were involved in this study consists of 18 males and 18 females for age difference and gender analysis. The PPG signals were taken in resting state by using pulse oximeter. The PPG signal was differentiated twice in order to form APG signal. These signals then undergo pre-processing and the segmentation process was done by using MATLAB. The highest peaks from the signal was used as reference point to determine the appropriate distance for one cycle of both signal. Then, the signals were classified by four commonly used classifiers which are Bayes Network, Naïve Bayes, Multilayer Perceptron, and Radial Basis Function. The outcome from this study suggested the accuracy up to 100% for different age group, 91.11% for female subjects and 95% for male subjects.
format Article
author Azam, Siti Nurfarah Ain
Sidek, Khairul Azami
Ismail, Ahmad Fadzil
author_facet Azam, Siti Nurfarah Ain
Sidek, Khairul Azami
Ismail, Ahmad Fadzil
author_sort Azam, Siti Nurfarah Ain
title Photoplethysmogram based biometric identification incorporating different age and gender group
title_short Photoplethysmogram based biometric identification incorporating different age and gender group
title_full Photoplethysmogram based biometric identification incorporating different age and gender group
title_fullStr Photoplethysmogram based biometric identification incorporating different age and gender group
title_full_unstemmed Photoplethysmogram based biometric identification incorporating different age and gender group
title_sort photoplethysmogram based biometric identification incorporating different age and gender group
publisher Faculty of Electronic and Computer Engineering (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM)
publishDate 2018
url http://irep.iium.edu.my/63236/7/63236%20%20Photoplethysmogram%20based%20biometric%20identification%20incorporating%20different%20age%20and%20gender%20group%20SCOPUS.pdf
http://irep.iium.edu.my/63236/13/63236%20%20Photoplethysmogram%20based%20biometric%20identification%20incorporating%20different%20age%20and%20gender%20group_article.pdf
http://irep.iium.edu.my/63236/
http://journal.utem.edu.my/index.php/jtec/article/view/3639/2634
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