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Data mining technique on Cardioid graph based ECG biometric authentication

Sidek, Khairul Azami and Sufi, Fahim and Khalil, Ibrahim (2011) Data mining technique on Cardioid graph based ECG biometric authentication. In: The Eighth IASTED International Conference on Biomedical Engineering (Biomed 2011), 16th - 18th February 2011, Innsbruck, Austria.

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Abstract

In this paper, a data mining technique is used on Cardioid based person identification mechanism using electrocardiogram (ECG). Recent studies in Cardioid based ECG biometric excites a new dimension of efficient patient authentication, which places new hope in faster patient care. However, existing research suffers from lower accuracy due to random biometric template selection from fixed points in Cartesian coordinate. In this paper, we have extracted the ECG features using set of Euclidean distances with the help of data mining techniques. Euclidean distances, being independent of fixed points (as opposed to existing research) maintains higher accuracy in biometric identification when Bayes Network was implemented for classification purposes. A total of 26 ECG recordings from MIT/BIH Normal Sinus Rhythm database (NSRDB) and MIT/BIH Arrythmia database (MITDB) are used for development and evaluation. Our experimentation on these two sets of public ECG databases shows the proposed data mining based approach on Euclidean distances obtained from Cardioid graph results to 98.60% and 98.30% classification accuracy respectively.

Item Type: Conference or Workshop Item (Full Paper)
Additional Information: 4698/31999
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices > TK7885 Computer engineering
Kulliyyahs/Centres/Divisions/Institutes: Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User: Dr Khairul Azami Sidek
Date Deposited: 17 Sep 2013 09:14
Last Modified: 17 Sep 2013 09:14
URI: http://irep.iium.edu.my/id/eprint/31999

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