Compressed ECG biometric using cardioid graph based feature extraction

Iqbal, Fatema-tuz-Zohra and Sidek, Khairul Azami (2015) Compressed ECG biometric using cardioid graph based feature extraction. ARPN Journal of Engineering and Applied Sciences, 10 (22). pp. 17219-17224. ISSN 1819-6608

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Abstract

In this paper, a Cardioid graph based feature extraction technique is applied to perform compressed Electrocardiogram (ECG) biometric. To the best of our knowledge, Cardioid graph based method has not been implemented on compressed ECG before. Another merit of this methodology is that no decompression of the compressed ECG signal is necessary before the recognition step. The QRS complexes obtained from the ECG signal is compressed using Discrete Wavelet Transform (DWT), followed by the Cardioid graph retrieval procedure. Compression is performed in three decomposition levels and with the first two Daubechies wavelets. Classification is conducted on all the three levels using Multilayer Perceptron (MLP) Neural Network. Maximum compression of 87.5% is achieved with an accuracy rate of 93.75%. For compression rate of 85%, the identification rate obtained is 98.75%. The same highest recognition rate of 98.75% is attained both with non-compressed and compressed data. The classification accuracy rates suggest that compressed ECG biometric with Cardioid graph based feature extraction is feasible and is capable of producing a robust biometric system.

Item Type:	Article (Journal)
Additional Information:	4698/46654
Uncontrolled Keywords:	compressed ECG biometric, cardioid graph, discrete wavelet transform.
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 Dec 2015 16:47
Last Modified:	16 Nov 2017 17:45
URI:	http://irep.iium.edu.my/id/eprint/46654

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