Zhang, Bonan, Chen, Chao, Lee, Ickjai, Lee, Kyungmi, and Ong, Kok-Leong (2024) Clustering-based Evaluation Framework of Feature Extraction Approaches for ECG Biometric Authentication. In: Proceedings of the International Joint Conference on Neural Networks. From: IJCNN 2024: International Joint Conference on Neural Networks, 30 June- 5 July 2024, Yokohama, Japan.

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Abstract

In recent times, electrocardiogram signals have been leveraged for biometric verification. The efficacy of such authentication is reliant on the feature extraction from the electrocardiogram signals. A number of electrocardiogram feature extraction methods are currently available, but these methods may not be universally applicable in different dataset collection scenarios. To tackle this issue, this paper introduces a clustering-based framework to assess the feature extraction techniques for electrocardiogram biometrics. In this paper, the effectiveness of the framework is validated by using different electrocardiogram feature extraction techniques and different electrocardiogram databases. The framework provides important insights into electrocardiogram signal.

Item ID:	84920
Item Type:	Conference Item (Research - E1)
ISBN:	978-8-3503-5931-2
Related URLs:	https://ieeexplore.ieee.org/document/106...
Copyright Information:	© IEEE 2024.
Date Deposited:	19 Mar 2025 00:00
FoR Codes:	46 INFORMATION AND COMPUTING SCIENCES > 4604 Cybersecurity and privacy > 460402 Data and information privacy @ 100%
SEO Codes:	22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220405 Cybersecurity @ 100%
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