An Investigation of Ear-EEG Signals for a Novel Biometric Authentication System
Abstract
This work explores the feasibility of biometric authentication using EEG signals acquired through in-ear devices, commonly referred to as ear-EEG. Traditional EEG-based biometric systems, while secure, often suffer from low usability due to cumbersome scalp-based electrode setups. In this study, we propose a novel and practical framework leveraging ear-EEG signals as a user-friendly alternative for everyday biometric authentication. The system extracts an original combination of temporal and spectral features from ear-EEG signals and feeds them into a fully connected deep neural network for subject identification. Experimental results on the only currently available ear-EEG dataset suitable for different purposes, including biometric authentication, demonstrate promising performance, with an average accuracy of 82\% in a subject identification scenario. These findings confirm the potential of ear-EEG as a viable and deployable direction for next-generation real-world biometric systems.
Keywords
Cite
@article{arxiv.2507.12873,
title = {An Investigation of Ear-EEG Signals for a Novel Biometric Authentication System},
author = {Danilo Avola and Giancarlo Crocetti and Gian Luca Foresti and Daniele Pannone and Claudio Piciarelli and Amedeo Ranaldi},
journal= {arXiv preprint arXiv:2507.12873},
year = {2025}
}