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Poster Session A: Tuesday, August 12, 1:30 – 4:30 pm, de Brug & E‑Hall

Sampling Rate and Task Selection in EEG-Authentication

Polina Tapal¹, Morteza Ansarinia¹, Christine Schiltz; ¹University of Luxemburg

Presenter: Polina Tapal

EEG-based authentication is a promising security alternative, measuring unique neural patterns, but variability in sampling rate ($f_s$) across datasets can distort performance metrics. This study evaluates how fs normalisation impacts authentication accuracy by analysing multiple EEG datasets with differing $f_s$. Using machine learning classification pipeline, we show that optimal $f_s$ selection depends critically on task-specific neural dynamics: high-frequency gamma tasks require ≥500 Hz, while alpha-dominated paradigms perform well at 128 Hz, and auditory potentials remain stable even at 98 Hz. Notably, prefrontal tasks show inherent limitations unaffected by $f_s$. Findings emphasise the need for standardised paradigm-specific $f_s$ in EEG authentication to improve reproducibility and robustness. This work provides practical insights for optimising biometric systems and advancing EEG-based authentication.

Topic Area: Brain Networks & Neural Dynamics

Extended Abstract: Full Text PDF