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Cardioid graph based ECG biometric in varying physiological conditions using compressed QRS

Mohd Azam, Siti Nurfarah Ain and Zohra, Fatema-tuz and Sidek, Khairul Azami and Smolen, Magdalena (2020) Cardioid graph based ECG biometric in varying physiological conditions using compressed QRS. In: nternational Conference on Telecommunication, Electronic and Computer Engineering 2019, ICTEC 2019, 22nd - 24th Oct. 2019, Melaka, Malaysia..

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Abstract

This paper proposes a robust biometric identification system using compressed electrocardiogram (ECG) signal by varying physiological conditions. The ECG data were obtained by recording a total of 30 healthy subjects where they performed six regular daily activities repeatedly at a sampling frequency of 1000 Hz. Then, the QRS complexes are segmented by implementing Amplitude Based Technique (ABT) where it compares the amplitudes of ECG points to determine the R peak. The segmented QRS is then compressed for various levels by using Discrete Wavelet Transform (DWT) algorithms and first 3 Daubechies (db) wavelet are computed. Next, a Cardioid graph is generated. In order to verify the matching process, the classification is performed by using the Multilayer Perceptron (MLP) technique. The results show that by applying this method, the accuracy of the identification rate can be achieved as high as 96.4% even when the data file is compressed up to 73.3%. When the data file is compressed, the outcomes also demonstrate that the execution time is less compare to non-compressed data. Therefore, the biometric identification system can be implemented efficiently as there will be a lesser issue regarding the data storage, execution time and accuracy based on the outcome of the study.

Item Type: Conference or Workshop Item (Plenary Papers)
Additional Information: 4698/81980
Uncontrolled Keywords: Biometric identification systems, Compressed datum, Discrete wavelet transform algorithms, Electrocardiogram signal, Identification rates, Multi layer perceptron, Physiological condition, Sampling frequencies
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
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
Kulliyyah of Engineering
Depositing User: Assoc Prof Dr Khairul Azami Sidek
Date Deposited: 06 Aug 2020 08:34
Last Modified: 06 Aug 2020 08:34
URI: http://irep.iium.edu.my/id/eprint/81980

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