Finer-grained Affective Computing EEG Dataset (FACED)

该数据集包含了从123名受试者收集的脑电波数据，这些数据是通过按照国际10-20系统定位的32个电极获取的。受试者在观看28个不同的视频片段时产生了数据，这些视频片段旨在引发九种不同情感类别的反应。此外，该数据集被用于训练一个模型，该模型能够将情感分为三大类别：负面（0）、中性（1）和正面（2）。这项任务旨在从脑电波数据中进行情感分类。

This dataset contains electroencephalogram (EEG) data collected from 123 subjects, acquired using 32 electrodes positioned in accordance with the international 10-20 system. The data was recorded while the subjects watched 28 distinct video clips, which were designed to elicit responses associated with nine different emotional categories. Furthermore, this dataset has been utilized to train a model capable of classifying emotions into three major categories: negative (0), neutral (1), and positive (2). The core task of this dataset is emotion classification based on electroencephalogram data.