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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iium-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 E-ISSN 2289-8131 http://journal.utem.edu.my/index.php/jtec/article/view/3639/2634 |
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Digital Repository |
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Local University |
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International Islamic University Malaysia |
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| 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/ http://irep.iium.edu.my/63236/ 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 |
| first_indexed |
2023-09-18T21:29:42Z |
| last_indexed |
2023-09-18T21:29:42Z |
| _version_ |
1777412427840749568 |