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Cardioid graph based ECG biometric recognition incorporating physiological variability

Iqbal, Fatema-tuz-Zohra and Sidek, Khairul Azami (2014) Cardioid graph based ECG biometric recognition incorporating physiological variability. In: 2014 IEEE Student Conference on Research and Development (SCOReD), 16-17 December 2014, Park Royal, Batu Feringghi, Penang.

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This paper investigates ECG signal in different physiological conditions to identify different individuals. 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 was extracted employing the Cardioid graph method. In this model, features were extracted solely from the graph derived using QRS complexes. Subjects were recognized with Multilayer Perceptron. Results were obtained through two approaches. In the former procedure, classification was performed on the whole dataset consisting of both training and testing set, which produced 95.3% of correctly classified instances. In the later approach the training and testing set was predefined where correctly classified instances were 93.9%. These results confirm that subject identification at different physiological conditions with Cardioid graph based technique produces better classification rates than previous study using only QRS complex.

Item Type: Conference or Workshop Item (Full Paper)
Additional Information: 4698/41615 (ISBN: 978-1-4799-6427-7, DOI: 10.1109/SCORED.2014.7072961)
Uncontrolled Keywords: biometric; cardioid; ecg; physiological variability
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Assoc Prof Dr Khairul Azami Sidek
Date Deposited: 29 Apr 2015 14:40
Last Modified: 13 Mar 2016 16:40
URI: http://irep.iium.edu.my/id/eprint/41615

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