Welcome to the InfoSci Platform
Human Identification Using Electrocardiogram Signal as a Biometric Trait

Human Identification Using Electrocardiogram Signal as a Biometric Trait

Anwar E. Ibrahim, Salah Abdel-Mageid, Nadra Nada, Marwa A. Elshahed
Copyright: © 2022 |Volume: 11 |Issue: 3 |Pages: 17
ISSN: 2160-9772|EISSN: 2160-9799|EISBN13: 9781668440216|DOI: 10.4018/IJSDA.287113
Cite Article Cite Article

MLA

Ibrahim, Anwar E., et al. "Human Identification Using Electrocardiogram Signal as a Biometric Trait." IJSDA vol.11, no.3 2022: pp.1-17. http://doi.org/10.4018/IJSDA.287113

APA

Ibrahim, A. E., Abdel-Mageid, S., Nada, N., & Elshahed, M. A. (2022). Human Identification Using Electrocardiogram Signal as a Biometric Trait. International Journal of System Dynamics Applications (IJSDA), 11(3), 1-17. http://doi.org/10.4018/IJSDA.287113

Chicago

Ibrahim, Anwar E., et al. "Human Identification Using Electrocardiogram Signal as a Biometric Trait," International Journal of System Dynamics Applications (IJSDA) 11, no.3: 1-17. http://doi.org/10.4018/IJSDA.287113

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Biometrics is an interesting study due to the incredible progress in security. Electrocardiogram (ECG) signal analysis is an active research area for diagnoses. Various techniques have been proposed in human identification system based on ECG. This work investigates in ECG as a biometric trait which based on uniqueness represented by physiological and geometrical of ECG signal of person.In this paper, a proposed non-fiducial identification system is presented with comparative study using Radial Basis Functions (RBF) neural network, Back Propagation (BP) neural network and Support Vector Machine (SVM) as classification methods. The Discrete Wavelet Transform method is applied to extract features from the ECG signal. The experimental results show that the proposed scheme achieves high identification rate compared to the existing techniques. Furthermore, the two classifiers RBF and BP are integrated to achieve higher rate of human identification.