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
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Online Access: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
http://irep.iium.edu.my/46346/
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7292210
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Institution: Universiti Islam Antarabangsa Malaysia
Language: English
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spelling my.iium.irep.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 REM 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
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
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/46346/4/46346_Acceleration_plethysmogram_based_biometric_identification_Fullpaper.pdf
http://irep.iium.edu.my/46346/7/46346_Acceleration%20plethysmogram%20based_Scopus.pdf
http://irep.iium.edu.my/46346/
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7292210
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