Real time electrocardiogram identification with multi-modal machine learning algorithms

Waili, Tuerxun and Mohd Nor, Rizal and Sidek, Khairul Azami and Abdul Rahman, Abdul Wahab and Guven, Ghokan (2017) Real time electrocardiogram identification with multi-modal machine learning algorithms. In: 2nd International Conference of Reliable Information and Communication Technology (IRICT) 2017, 23rd-24th April 2017, Johor Bahru, Johor.

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Abstract

Weaknesses in conventional identification technologies such as identification cards, badges and RFID tags prompts attention to biometric form of identification. Biometrics like voice, brain signal and finger print are unique human traits that can be used for identification. In this paper we present an identification system based on Electrocardiogram (heart signal). There is a considerable number of research in the past with high accuracy for identification, however, most ignore the practical time required to identify an individual. In this study, we explored a more practical approach in identification by reducing the number of time required for identification. We explore ways to identity a person within 3–4 s using just 5 heart beats. We extracted few reliable features from each QRS complexes, combined effort of three algorithms to achieve 96% accuracy. This approach is more suitable and practical in real time applications where time for identification is important.

Item Type:	Conference or Workshop Item (Plenary Papers)
Additional Information:	4698/60819
Uncontrolled Keywords:	SVM, Random forest, Logistic regression, QRS complex, ECG biometric, Identification
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 Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Assoc Prof Dr Khairul Azami Sidek
Date Deposited:	03 Jan 2018 16:26
Last Modified:	20 Feb 2019 16:09
URI:	http://irep.iium.edu.my/id/eprint/60819

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