Biometric recognition for twins inconsideration of age variability using PPG signals
Recent biometric modalities involve biomedical signals such as PPG to identify individuals. This study has been motivated by this new research area using PPG signal to identify twins incorporating age variability. The proposed system is suggested to be a substitute to the current traditional methods...
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| Format: | Article |
| Language: | English English |
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Faculty of Electronic and Computer Engineering (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM)
2018
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| Online Access: | http://irep.iium.edu.my/63235/ http://irep.iium.edu.my/63235/1/3638-10061-1-PB.pdf http://irep.iium.edu.my/63235/7/63235%20Biometric%20recognition%20for%20twins%20inconsideration%20of%20age%20variability%20using%20PPG%20signals%20SCOPUS.pdf |
| _version_ | 1848785998665744384 |
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| author | Mohammed Nadzri, Nur Izzati Sidek, Khairul Azami Ismail, Ahmad Fadzil |
| author_facet | Mohammed Nadzri, Nur Izzati Sidek, Khairul Azami Ismail, Ahmad Fadzil |
| author_sort | Mohammed Nadzri, Nur Izzati |
| building | IIUM Repository |
| collection | Online Access |
| description | Recent biometric modalities involve biomedical signals such as PPG to identify individuals. This study has been motivated by this new research area using PPG signal to identify twins incorporating age variability. The proposed system is suggested to be a substitute to the current traditional methods being used widely nowadays. A total of 21 subjects were used for experimentation purposes and lowpass filter is applied to remove unwanted noise from the signal. Distinctive features are extracted from the filtered PPG signals. Later, Bayes Network (BN), Naive Bayes (NB), Radial Basis Function (RBF) and Multilayer Perceptron (MLP) were used to classify the subjects using the discriminant features. Based on the experimentation results, classification accuracies ranging from 90% to 100% were achieved by categorizing the data into six different sets which are overall dataset, Groups I, II, III, IV and V. The result provides an alternative mechanism to identify twins using PPG signals incorporating age variability besides using the traditional methods. |
| first_indexed | 2025-11-14T17:02:03Z |
| format | Article |
| id | iium-63235 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:02:03Z |
| publishDate | 2018 |
| publisher | Faculty of Electronic and Computer Engineering (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-632352018-04-18T01:00:17Z http://irep.iium.edu.my/63235/ Biometric recognition for twins inconsideration of age variability using PPG signals Mohammed Nadzri, Nur Izzati Sidek, Khairul Azami Ismail, Ahmad Fadzil TK7885 Computer engineering Recent biometric modalities involve biomedical signals such as PPG to identify individuals. This study has been motivated by this new research area using PPG signal to identify twins incorporating age variability. The proposed system is suggested to be a substitute to the current traditional methods being used widely nowadays. A total of 21 subjects were used for experimentation purposes and lowpass filter is applied to remove unwanted noise from the signal. Distinctive features are extracted from the filtered PPG signals. Later, Bayes Network (BN), Naive Bayes (NB), Radial Basis Function (RBF) and Multilayer Perceptron (MLP) were used to classify the subjects using the discriminant features. Based on the experimentation results, classification accuracies ranging from 90% to 100% were achieved by categorizing the data into six different sets which are overall dataset, Groups I, II, III, IV and V. The result provides an alternative mechanism to identify twins using PPG signals incorporating age variability besides using the traditional methods. Faculty of Electronic and Computer Engineering (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM) 2018 Article PeerReviewed application/pdf en http://irep.iium.edu.my/63235/1/3638-10061-1-PB.pdf application/pdf en http://irep.iium.edu.my/63235/7/63235%20Biometric%20recognition%20for%20twins%20inconsideration%20of%20age%20variability%20using%20PPG%20signals%20SCOPUS.pdf Mohammed Nadzri, Nur Izzati and Sidek, Khairul Azami and Ismail, Ahmad Fadzil (2018) Biometric recognition for twins inconsideration of age variability using PPG signals. Journal of Telecommunication, Electronic and Computer Engineering, 10 (1-5). pp. 97-100. ISSN 2180-1843 E-ISSN 2289-8131 http://journal.utem.edu.my/index.php/jtec/article/view/3638/2633 |
| spellingShingle | TK7885 Computer engineering Mohammed Nadzri, Nur Izzati Sidek, Khairul Azami Ismail, Ahmad Fadzil Biometric recognition for twins inconsideration of age variability using PPG signals |
| title | Biometric recognition for twins inconsideration of age variability using PPG signals |
| title_full | Biometric recognition for twins inconsideration of age variability using PPG signals |
| title_fullStr | Biometric recognition for twins inconsideration of age variability using PPG signals |
| title_full_unstemmed | Biometric recognition for twins inconsideration of age variability using PPG signals |
| title_short | Biometric recognition for twins inconsideration of age variability using PPG signals |
| title_sort | biometric recognition for twins inconsideration of age variability using ppg signals |
| topic | TK7885 Computer engineering |
| url | http://irep.iium.edu.my/63235/ http://irep.iium.edu.my/63235/ http://irep.iium.edu.my/63235/1/3638-10061-1-PB.pdf http://irep.iium.edu.my/63235/7/63235%20Biometric%20recognition%20for%20twins%20inconsideration%20of%20age%20variability%20using%20PPG%20signals%20SCOPUS.pdf |