Acceleration plethysmogram based biometric identification

This paper presents the feasibility study of Acceleration Plethysmogram (APG) based biometric identification system. APG signals are obtained from the second derivative of the Photoplethysmogram (PPG) signal. It has been reported from previous literature that APG signals contain more information as...

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Main Authors:	Jaafar, Nur Azua Liyana, Sidek, Khairul Azami, Mohd Azam, Siti Nurfarah Ain
Format:	Conference or Workshop Item
Language:	English English
Published:	IEEE 2015
Subjects:	TK7885 Computer engineering
Online Access:	http://irep.iium.edu.my/46346/ http://irep.iium.edu.my/46346/ http://irep.iium.edu.my/46346/ http://irep.iium.edu.my/46346/4/46346_Acceleration_plethysmogram_based_biometric_identification_Fullpaper.pdf http://irep.iium.edu.my/46346/7/46346_Acceleration%20plethysmogram%20based_Scopus.pdf

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spelling	iium-463462017-09-23T06:43:42Z http://irep.iium.edu.my/46346/ Acceleration plethysmogram based biometric identification Jaafar, Nur Azua Liyana Sidek, Khairul Azami Mohd Azam, Siti Nurfarah Ain TK7885 Computer engineering This paper presents the feasibility study of Acceleration Plethysmogram (APG) based biometric identification system. APG signals are obtained from the second derivative of the Photoplethysmogram (PPG) signal. It has been reported from previous literature that APG signals contain more information as compared to the PPG signal. Thus, in this paper, the robustness and reliability of APG signal as a biometric recognition mechanism will be proven. APG signals of 10 subjects were acquired from the Multiparameter Intelligent Monitoring in Intensive Care II Waveform Database (MIMIC2WDB) which contains PPG signals with a sampling frequency of 125 Hz. The signals were later converted into an APG waveform. Then, discriminating features are extracted from the APG morphology. Finally, these APG samples were classified using commonly known classification techniques to identify individuals. Based on the experimentation results, APG signal when using Bayes Network gives an identification rate of 97.5 percentage as compared to PPG signal of 55 percentage for the same waveform. This outcome suggests the feasibility and robustness of APG signals as a biometric modality as compared to PPG signals. IEEE 2015 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/46346/4/46346_Acceleration_plethysmogram_based_biometric_identification_Fullpaper.pdf application/pdf en http://irep.iium.edu.my/46346/7/46346_Acceleration%20plethysmogram%20based_Scopus.pdf Jaafar, Nur Azua Liyana and Sidek, Khairul Azami and Mohd Azam, Siti Nurfarah Ain (2015) Acceleration plethysmogram based biometric identification. In: 2015 International Conference on BioSignal Analysis, Processing and Systems (ICBAPS 2015), 26-28 May 2015, Kuala Lumpur. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7292210 10.1109/ICBAPS.2015.7292210
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 Jaafar, Nur Azua Liyana Sidek, Khairul Azami Mohd Azam, Siti Nurfarah Ain Acceleration plethysmogram based biometric identification
description	This paper presents the feasibility study of Acceleration Plethysmogram (APG) based biometric identification system. APG signals are obtained from the second derivative of the Photoplethysmogram (PPG) signal. It has been reported from previous literature that APG signals contain more information as compared to the PPG signal. Thus, in this paper, the robustness and reliability of APG signal as a biometric recognition mechanism will be proven. APG signals of 10 subjects were acquired from the Multiparameter Intelligent Monitoring in Intensive Care II Waveform Database (MIMIC2WDB) which contains PPG signals with a sampling frequency of 125 Hz. The signals were later converted into an APG waveform. Then, discriminating features are extracted from the APG morphology. Finally, these APG samples were classified using commonly known classification techniques to identify individuals. Based on the experimentation results, APG signal when using Bayes Network gives an identification rate of 97.5 percentage as compared to PPG signal of 55 percentage for the same waveform. This outcome suggests the feasibility and robustness of APG signals as a biometric modality as compared to PPG signals.
format	Conference or Workshop Item
author	Jaafar, Nur Azua Liyana Sidek, Khairul Azami Mohd Azam, Siti Nurfarah Ain
author_facet	Jaafar, Nur Azua Liyana Sidek, Khairul Azami Mohd Azam, Siti Nurfarah Ain
author_sort	Jaafar, Nur Azua Liyana
title	Acceleration plethysmogram based biometric identification
title_short	Acceleration plethysmogram based biometric identification
title_full	Acceleration plethysmogram based biometric identification
title_fullStr	Acceleration plethysmogram based biometric identification
title_full_unstemmed	Acceleration plethysmogram based biometric identification
title_sort	acceleration plethysmogram based biometric identification
publisher	IEEE
publishDate	2015
url	http://irep.iium.edu.my/46346/ http://irep.iium.edu.my/46346/ http://irep.iium.edu.my/46346/ http://irep.iium.edu.my/46346/4/46346_Acceleration_plethysmogram_based_biometric_identification_Fullpaper.pdf http://irep.iium.edu.my/46346/7/46346_Acceleration%20plethysmogram%20based_Scopus.pdf
first_indexed	2023-09-18T21:05:59Z
last_indexed	2023-09-18T21:05:59Z
_version_	1777410936069423104

Acceleration plethysmogram based biometric identification

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