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. 2026 Jan 30;16:6674. doi: 10.1038/s41598-026-36840-4

Table 13.

Comparison with state-of-the-art EEG-based biometric systems.

Study Approach Reported accuracy Paradigm
Roy et al.8 CNN-based deep learning >95% Task-related EEG
Zhang et al.21 CNN + RNN hybrid 96–97% Resting state
Thomas et al.3 Multimodal (EEG + ECG) Inline graphic98% Event-related potentials
Arnau et al.24 Brain Encoding Dataset (BED) release 88 Resting, cognitive, and VEP/VEPC
This work Lenient PREP + MFCC + XGBoost 98.0% VEPC 10 Hz

Bold indicates the best/ maximum reported identification accuracy among the compared state-of-the-art methods.