Filip Postepski, Grzegorz M. Wojcik · 2026 · arXiv
DOI: 10.48550/arXiv.2610.28442 · open-access PDF
이 연구는 짧고 최소한의 사전 처리된 EEG 세그먼트가 Myers-Briggs Type Indicator (MBTI)에 따라 외환 또는 내향으로 분류되는 개인을 구별할 수있는 충분한 정보를 포함하는지 여부를 검사합니다. 50 참가자의 EEG 기록은 4 개의 세그먼트로 나누어 4 개의 주제 독립적 인 5 배 교차 검증 절차를 사용하여 분석하여 EEGNet, EEGProgress 및 새롭게 제안 된 컴팩트한 구동 아키텍처 SSCNet를 비교했습니다. SSCNet는 가장 높은 평균 정확도를 달성했습니다 (0.6481), AUC (0.7063), 및 F1 점수 (0.6276).
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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