Filip Postepski, Grzegorz M. Wojcik · 2026 · arXiv
DOI: 10.48550/arXiv.2610.28442 · open-access PDF
Este estudo examina se os segmentos de EEG curtos, minimamente pré-processados contêm informações suficientes para distinguir entre indivíduos classificados como extrovertidos ou introvertidos de acordo com o Indicador de Tipo de Myers-Briggs (MBTI). as gravações de EEG de 50 participantes foram divididas em 4 segmentos e analisadas usando um procedimento de validação cruzada de 5 vezes para comparar EEGNet, EEGProgress e uma arquitetura convolucional compacta recém-proposta, SSCNet.
Machine translation (Meta M2M100); the English original follows.
This study examines whether short, minimally preprocessed EEG segments contain sufficient information to distinguish between individuals classified as extraverted or introverted according to the Myers--Briggs Type Indicator (MBTI). EEG recordings from 50 participants were divided into 4-s segments and analyzed using a subject-independent nested 5-fold cross-validation procedure to compare EEGNet, EEGProgress, and a newly proposed compact convolutional architecture, SSCNet. SSCNet achieved the highest mean accuracy (0.6481), AUC (0.7063), and F1-score (0.6276). The proposed architecture also sh
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