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Feature extraction for biometric recognition with photoplethysmography signals

Proceeding of The 21st Signal Processing and Communications Applications Conference (SIU 2013) at Haspolat, Turkey on 24 April 2013 through 26 April 2013. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp?tag=1

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Bibliographic Details
Main Authors: Resit Kavsaoglu, A., Polat, Kemal, Recep Bozkure, M., Hariharan, Muthusamy, Dr.
Other Authors: kavsaoglu@sinop.edu.tr
Format: Working Paper
Language:other
Published: IEEE Conference Publications 2014
Subjects:
Biometrics
Classification
Derivatives
Feature extraction
Identification
Photoplethysmography (PPG)
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/34984
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spelling my.unimap-349842014-06-02T08:39:44Z Feature extraction for biometric recognition with photoplethysmography signals Resit Kavsaoglu, A. Polat, Kemal Recep Bozkure, M. Hariharan, Muthusamy, Dr. kavsaoglu@sinop.edu.tr kpolat@ibu.edu.tr mbozkurt@sakarya.edu.tr hari@unimap.edu.my Biometrics Classification Derivatives Feature extraction Identification Photoplethysmography (PPG) Proceeding of The 21st Signal Processing and Communications Applications Conference (SIU 2013) at Haspolat, Turkey on 24 April 2013 through 26 April 2013. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp?tag=1 Photoplethysmography (PPG) signals stand out due to features such as readily accessible, high reliability and confidentiality, the ease of use etc. among bio-signals. The feasibility studies carried out on the PPG signals demonstrated that PPG signals contained important features for human recognition and were the availability of biometric identification systems. In this study, twenty new features were extracted from PPG signal as a preliminary study intended to biometric recognition. PPG signals with 10 seconds were recorded from five healthy people using SDPPG (second derivative PPG) data acquisition card. To remove the noise from received raw PPG signals, a FIR low pass filtering with 200 points and 10 Hz cut-off frequency was designed. These twenty new features were obtained from filtered PPG signal and its second derivative. PPG signal with 10 seconds contains eight periods and twenty characteristic features in each person must not change within an individual over a period. This feature symbolizes the consistency in the identification of a person. To test the performance of biometrie recognition system, the k-NN (k-nearest neighbor) classifier was used and achieved 95% of recognition success rate using lO-fold cross validation with twenty new features. The obtained results showed that the developed biometric recognition system based on PPG signal were very promising. 2014-06-02T08:39:44Z 2014-06-02T08:39:44Z 2013-04 Working Paper p.1-4 978-1-4673-5562-9 (Print) http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6531568&tag=1 http://dspace.unimap.edu.my:80/dspace/handle/123456789/34984 http://dx.doi.org/10.1109/SIU.2013.6531568 978-1-4673-5561-2 (Online) other Proceeding of The 21st Signal Processing and Communications Applications Conference (SIU 2013); IEEE Conference Publications
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language other
topic Biometrics
Classification
Derivatives
Feature extraction
Identification
Photoplethysmography (PPG)
spellingShingle Biometrics
Classification
Derivatives
Feature extraction
Identification
Photoplethysmography (PPG)
Resit Kavsaoglu, A.
Polat, Kemal
Recep Bozkure, M.
Hariharan, Muthusamy, Dr.
Feature extraction for biometric recognition with photoplethysmography signals
description Proceeding of The 21st Signal Processing and Communications Applications Conference (SIU 2013) at Haspolat, Turkey on 24 April 2013 through 26 April 2013. Link to publisher's homepage at http://ezproxy.unimap.edu.my:2080/Xplore/dynhome.jsp?tag=1
author2 kavsaoglu@sinop.edu.tr
author_facet kavsaoglu@sinop.edu.tr
Resit Kavsaoglu, A.
Polat, Kemal
Recep Bozkure, M.
Hariharan, Muthusamy, Dr.
format Working Paper
author Resit Kavsaoglu, A.
Polat, Kemal
Recep Bozkure, M.
Hariharan, Muthusamy, Dr.
author_sort Resit Kavsaoglu, A.
title Feature extraction for biometric recognition with photoplethysmography signals
title_short Feature extraction for biometric recognition with photoplethysmography signals
title_full Feature extraction for biometric recognition with photoplethysmography signals
title_fullStr Feature extraction for biometric recognition with photoplethysmography signals
title_full_unstemmed Feature extraction for biometric recognition with photoplethysmography signals
title_sort feature extraction for biometric recognition with photoplethysmography signals
publisher IEEE Conference Publications
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/34984
_version_ 1643797474167488512
score 13.222552

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