Enhancement of low sampling frequency recordings for ECG biometric matching using interpolation

Enhancement of low sampling frequency recordings for ECG biometric matching using interpolation

Electrocardiogram (ECG) based biometric matching suffers from high misclassification error with lower sampling frequency data. This situation may lead to an unreliable and vulnerable identity authentication process in high security applications. In this paper, quality enhancement techniques for ECG...

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Main Authors: Sidek, Khairul Azami, Khalil, Ibrahim
Format: Article
Language:English
Published: Elsevier 2013
Subjects:
TK7885 Computer engineering
Online Access:http://irep.iium.edu.my/31985/
http://irep.iium.edu.my/31985/
http://irep.iium.edu.my/31985/
http://irep.iium.edu.my/31985/1/sidek_etal13.pdf
id iium-31985
recordtype eprints
spelling iium-319852013-10-14T00:53:37Z http://irep.iium.edu.my/31985/ Enhancement of low sampling frequency recordings for ECG biometric matching using interpolation Sidek, Khairul Azami Khalil, Ibrahim TK7885 Computer engineering Electrocardiogram (ECG) based biometric matching suffers from high misclassification error with lower sampling frequency data. This situation may lead to an unreliable and vulnerable identity authentication process in high security applications. In this paper, quality enhancement techniques for ECG data with low sampling frequency has been proposed for person identification based on piecewise cubic Hermite interpolation (PCHIP) and piecewise cubic spline interpolation (SPLINE). A total of 70 ECG recordings from 4 different public ECG databases with 2 different sampling frequencies were applied for development and performance comparison purposes. An analytical method was used for feature extraction. The ECG recordings were segmented into two parts: the enrolment and recognition datasets. Three biometric matching methods, namely, Cross Correlation (CC), Percent Root-Mean-Square Deviation (PRD) and Wavelet Distance Measurement (WDM) were used for performance evaluation before and after applying interpolation techniques. Results of the experiments suggest that biometric matching with interpolated ECG data on average achieved higher matching percentage value of up to 4% for CC, 3% for PRD and 94% for WDM. These results are compared with the existing method when using ECG recordings with lower sampling frequency. Moreover, increasing the sample size from 56 to 70 subjects improves the results of the experiment by 4% for CC, 14.6% for PRD and 0.3% for WDM. Furthermore, higher classification accuracy of up to 99.1% for PCHIP and 99.2% for SPLINE with interpolated ECG data as compared of up to 97.2% without interpolation ECG data verifies the study claim that applying interpolation techniques enhances the quality of the ECG data. Elsevier 2013-01 Article PeerReviewed application/pdf en http://irep.iium.edu.my/31985/1/sidek_etal13.pdf Sidek, Khairul Azami and Khalil, Ibrahim (2013) Enhancement of low sampling frequency recordings for ECG biometric matching using interpolation. Computer Methods and Programs in Biomedicine, 109 (1). pp. 13-25. ISSN 0169-2607 http://www.sciencedirect.com/science/article/pii/S016926071200212X 10.1016/j.cmpb.2012.08.015
repository_type Digital Repository
institution_category Local University
institution International Islamic University Malaysia
building IIUM Repository
collection Online Access
language English
topic TK7885 Computer engineering
spellingShingle TK7885 Computer engineering
Sidek, Khairul Azami
Khalil, Ibrahim
Enhancement of low sampling frequency recordings for ECG biometric matching using interpolation
description Electrocardiogram (ECG) based biometric matching suffers from high misclassification error with lower sampling frequency data. This situation may lead to an unreliable and vulnerable identity authentication process in high security applications. In this paper, quality enhancement techniques for ECG data with low sampling frequency has been proposed for person identification based on piecewise cubic Hermite interpolation (PCHIP) and piecewise cubic spline interpolation (SPLINE). A total of 70 ECG recordings from 4 different public ECG databases with 2 different sampling frequencies were applied for development and performance comparison purposes. An analytical method was used for feature extraction. The ECG recordings were segmented into two parts: the enrolment and recognition datasets. Three biometric matching methods, namely, Cross Correlation (CC), Percent Root-Mean-Square Deviation (PRD) and Wavelet Distance Measurement (WDM) were used for performance evaluation before and after applying interpolation techniques. Results of the experiments suggest that biometric matching with interpolated ECG data on average achieved higher matching percentage value of up to 4% for CC, 3% for PRD and 94% for WDM. These results are compared with the existing method when using ECG recordings with lower sampling frequency. Moreover, increasing the sample size from 56 to 70 subjects improves the results of the experiment by 4% for CC, 14.6% for PRD and 0.3% for WDM. Furthermore, higher classification accuracy of up to 99.1% for PCHIP and 99.2% for SPLINE with interpolated ECG data as compared of up to 97.2% without interpolation ECG data verifies the study claim that applying interpolation techniques enhances the quality of the ECG data.
format Article
author Sidek, Khairul Azami
Khalil, Ibrahim
author_facet Sidek, Khairul Azami
Khalil, Ibrahim
author_sort Sidek, Khairul Azami
title Enhancement of low sampling frequency recordings for ECG biometric matching using interpolation
title_short Enhancement of low sampling frequency recordings for ECG biometric matching using interpolation
title_full Enhancement of low sampling frequency recordings for ECG biometric matching using interpolation
title_fullStr Enhancement of low sampling frequency recordings for ECG biometric matching using interpolation
title_full_unstemmed Enhancement of low sampling frequency recordings for ECG biometric matching using interpolation
title_sort enhancement of low sampling frequency recordings for ecg biometric matching using interpolation
publisher Elsevier
publishDate 2013
url http://irep.iium.edu.my/31985/
http://irep.iium.edu.my/31985/
http://irep.iium.edu.my/31985/
http://irep.iium.edu.my/31985/1/sidek_etal13.pdf
first_indexed 2023-09-18T20:46:09Z
last_indexed 2023-09-18T20:46:09Z
_version_ 1777409688013373440

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