Publication: Design and implementation of an access control based on electrocardiogram (ECG) biometric system
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Date
2024-08
Authors
Anis Nadirah binti Suaidi
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Abstract
Technological advancements have placed individual security at risk due to the forging of traditional access control methods. Consequently, biometric systems have emerged as a more secure alternative. Among these, the electrocardiogram (ECG) offers a unique identifier for every person, enhancing security through its resistance to forgery or duplication, and providing health information. This project proposes a robust biometric authentication system using ECG signals processed by the PanTompkins algorithm for noise reduction and fiducial point extraction, followed by classification with Artificial Neural Network (ANN). The ANN, trained with ECG samples from 10 users, achieved a classification accuracy of 97.4%, demonstrating the system effectiveness. This integration allows for seamless hardware control, ensuring secure and efficient access control. The results highlight the potential for ECG based authentication in real-world applications, providing both high accuracy and practicality.