A comparative analysis of QRS and cardioid graph based ECG biometric recognition in different physiological conditions

This paper performs a comparative analysis of QRS and Cardioid Graph Based ECG Biometric Recognition incorporating Physiological variability. Data was acquired from 30 subjects, where each subject performed six types of physical activities namely walking, going upstairs, going downstairs, natural g...

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Main Authors:	Iqbal, Fatema-tuz-Zohra, Sidek, Khairul Azami, Noah, Nor Afifah, Gunawan, Teddy Surya
Format:	Conference or Workshop Item
Language:	English English English English
Published:	IEEE 2014
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://irep.iium.edu.my/40299/ http://irep.iium.edu.my/40299/ http://irep.iium.edu.my/40299/1/1570040383.pdf http://irep.iium.edu.my/40299/2/TitlePage.pdf http://irep.iium.edu.my/40299/3/TOC.pdf http://irep.iium.edu.my/40299/11/40299_A%20comparative%20analysis%20of%20QRS_scopus.pdf

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recordtype	eprints
spelling	iium-402992017-09-19T11:55:35Z http://irep.iium.edu.my/40299/ A comparative analysis of QRS and cardioid graph based ECG biometric recognition in different physiological conditions Iqbal, Fatema-tuz-Zohra Sidek, Khairul Azami Noah, Nor Afifah Gunawan, Teddy Surya TK Electrical engineering. Electronics Nuclear engineering This paper performs a comparative analysis of QRS and Cardioid Graph Based ECG Biometric Recognition incorporating Physiological variability. Data was acquired from 30 subjects, where each subject performed six types of physical activities namely walking, going upstairs, going downstairs, natural gait, lying with position changed and resting while watching TV. Then from the signals of these physiological conditions specific features exclusive to each subject were extracted employing the Cardioid graph based model. In this model, features were extracted solely from the graph derived of the QRS complexes. Subjects were recognized with Multilayer Perceptron classification algorithm. Results were obtained through two approaches. Classification was performed on the whole dataset, Cardioid graph based method resulted in 96.4% of correctly classified instances, whereas QRS complex based ECG produced 94.7% accuracy rates. Later, sensitivity and specificity analysis was done to determine the robustness of the model which produced higher outcomes for Cardioid graph based technique of 96.4% and 99.9% respectively. These results suggest that subject identification in different physiological conditions with Cardioid graph based technique produces better classification rates than that of employing only QRS complexes. IEEE 2014-11-25 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/40299/1/1570040383.pdf application/pdf en http://irep.iium.edu.my/40299/2/TitlePage.pdf application/pdf en http://irep.iium.edu.my/40299/3/TOC.pdf application/pdf en http://irep.iium.edu.my/40299/11/40299_A%20comparative%20analysis%20of%20QRS_scopus.pdf Iqbal, Fatema-tuz-Zohra and Sidek, Khairul Azami and Noah, Nor Afifah and Gunawan, Teddy Surya (2014) A comparative analysis of QRS and cardioid graph based ECG biometric recognition in different physiological conditions. In: IEEE International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA2014), 25-27 November 2014, Kuala Lumpur. http://ieeemy-ims.org/icsima/14/
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English English English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Iqbal, Fatema-tuz-Zohra Sidek, Khairul Azami Noah, Nor Afifah Gunawan, Teddy Surya A comparative analysis of QRS and cardioid graph based ECG biometric recognition in different physiological conditions
description	This paper performs a comparative analysis of QRS and Cardioid Graph Based ECG Biometric Recognition incorporating Physiological variability. Data was acquired from 30 subjects, where each subject performed six types of physical activities namely walking, going upstairs, going downstairs, natural gait, lying with position changed and resting while watching TV. Then from the signals of these physiological conditions specific features exclusive to each subject were extracted employing the Cardioid graph based model. In this model, features were extracted solely from the graph derived of the QRS complexes. Subjects were recognized with Multilayer Perceptron classification algorithm. Results were obtained through two approaches. Classification was performed on the whole dataset, Cardioid graph based method resulted in 96.4% of correctly classified instances, whereas QRS complex based ECG produced 94.7% accuracy rates. Later, sensitivity and specificity analysis was done to determine the robustness of the model which produced higher outcomes for Cardioid graph based technique of 96.4% and 99.9% respectively. These results suggest that subject identification in different physiological conditions with Cardioid graph based technique produces better classification rates than that of employing only QRS complexes.
format	Conference or Workshop Item
author	Iqbal, Fatema-tuz-Zohra Sidek, Khairul Azami Noah, Nor Afifah Gunawan, Teddy Surya
author_facet	Iqbal, Fatema-tuz-Zohra Sidek, Khairul Azami Noah, Nor Afifah Gunawan, Teddy Surya
author_sort	Iqbal, Fatema-tuz-Zohra
title	A comparative analysis of QRS and cardioid graph based ECG biometric recognition in different physiological conditions
title_short	A comparative analysis of QRS and cardioid graph based ECG biometric recognition in different physiological conditions
title_full	A comparative analysis of QRS and cardioid graph based ECG biometric recognition in different physiological conditions
title_fullStr	A comparative analysis of QRS and cardioid graph based ECG biometric recognition in different physiological conditions
title_full_unstemmed	A comparative analysis of QRS and cardioid graph based ECG biometric recognition in different physiological conditions
title_sort	comparative analysis of qrs and cardioid graph based ecg biometric recognition in different physiological conditions
publisher	IEEE
publishDate	2014
url	http://irep.iium.edu.my/40299/ http://irep.iium.edu.my/40299/ http://irep.iium.edu.my/40299/1/1570040383.pdf http://irep.iium.edu.my/40299/2/TitlePage.pdf http://irep.iium.edu.my/40299/3/TOC.pdf http://irep.iium.edu.my/40299/11/40299_A%20comparative%20analysis%20of%20QRS_scopus.pdf
first_indexed	2023-09-18T20:57:48Z
last_indexed	2023-09-18T20:57:48Z
_version_	1777410421181906944

A comparative analysis of QRS and cardioid graph based ECG biometric recognition in different physiological conditions

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