Title: Gender-based analysis of ECG biometric identification under different physiological conditions

Authors: Siti Nurfarah Ain Mohd Azam; Khairul Azami Sidek

Addresses: Department of Electrical and Computer Engineering, Faculty of Engineering, International Islamic University Malaysia, Malaysia ' Department of Electrical and Computer Engineering, Faculty of Engineering, International Islamic University Malaysia, Malaysia

Abstract: The study investigates the reliability of ECG signals as a biometric feature for individuals in different physiological conditions. Previous research has shown that ECG biometric identification can be performed during normal conditions, however, the challenge lies in performing biometric identification on moving subjects. Therefore, this work proposed a robust biometric identification by using ECG signals incorporating different physiological conditions based on gender. A total of 15 male subjects and 7 female subjects who performed sitting, walking and running activities were involved in this work. The study discovered that ECG signals can be reliably used as a biometric for different physiological conditions, with medium Gaussian SVM being the most effective with the results of 98.7%. The accuracy of ECG signal classification can be affected by gender differences, with female subjects exhibiting accuracy as low as 82.9%, likely due to the size of their hearts.

Keywords: ECG; biometric; person identification; pattern recognition; verification; signal processing; human authentication; support vector machine; biological signals; signal classification.

DOI: 10.1504/IJBM.2025.148283

International Journal of Biometrics, 2025 Vol.17 No.5, pp.433 - 448

Accepted: 21 Oct 2024
Published online: 01 Sep 2025 *

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