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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Main Authors:	Mohammed Nadzri, Nur Izzati, 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
Subjects:	TK7885 Computer engineering
Online Access:	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

id	iium-63235
recordtype	eprints
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
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TK7885 Computer engineering
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
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.
format	Article
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
title	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_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_sort	biometric recognition for twins inconsideration of age variability using ppg signals
publisher	Faculty of Electronic and Computer Engineering (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM)
publishDate	2018
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
first_indexed	2023-09-18T21:29:41Z
last_indexed	2023-09-18T21:29:41Z
_version_	1777412427697094656

Biometric recognition for twins inconsideration of age variability using PPG signals

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