Power spectral analysis of occipital area during eyes-closed and eyes-open
DOI:
https://doi.org/10.24265/liberabit.2025.v31n2.1085Keywords:
Power spectral analysis, EEG, logistic regression, asymmetry index, FFTAbstract
Background: Power spectral analysis of the occipital cortex is essential for characterizing brain activity during attentional and relaxed states. Objectives: This study aims to develop a predictive model capable of distinguishing between eyes-closed (EC) and eyes-open (EO) states using only two electrodes (O1 and O2), through analysis of power spectral density (PSD) and an interhemispheric asymmetry index. Method: EEG recordings from 33 seventh- and eighth-grade students were processed using the Fast Fourier Transform (FFT) and analyzed with a logistic regression model employing a Cauchit link function. Results: The model yielded an AUC of 84.2%, with satisfactory precision and sensitivity. While the asymmetry index alone was not highly predictive, it significantly improved performance when combined with frequency-band features. Conclusions: This minimal EEG setup demonstrates reliable performance in distinguishing ocular states in non-clinical environments. The approach suggests potential applications in educational and field contexts, emphasizing the value of low-cost EEG solutions in cognitive monitoring.
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Copyright (c) 2025 Adolfo González-González , Diego Gallardo , Yolanda Gómez, Marc Zeise

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