EmoEEG-MC: A Multi-Context Emotional EEG Dataset for Cross-Context Emotion Decoding

We present the Multi-Context Emotional EEG (EmoEEG-MC) dataset, featuring 64-channel EEG and peripheral physiological data from 60 participants exposed to two distinct contexts: video-induced and imagery-induced emotions. These contexts evoke seven distinct emotional categories: joy, inspiration, tenderness, fear, disgust, sadness, and neutral emotion. The emotional experience of a specific emotion category was validated through subjective reports. The EmoEEG-MC dataset serves as a foundational resource for advancing cross-context emotion recognition and enhancing the real-world application of emotion decoding methods.

本研究提出了多情境情感脑电（Multi-Context Emotional EEG, EmoEEG-MC）数据集，该数据集涵盖60名被试的64通道脑电（Electroencephalogram, EEG）与外周生理数据，所有被试均处于两种不同的情绪诱发情境：视频诱发情境与想象诱发情境。上述两种情境可诱发七种明确的情绪类别：快乐、灵感、温柔、恐惧、厌恶、悲伤以及中性情绪。特定情绪类别的主观情绪体验，均通过被试的主观报告完成验证。EmoEEG-MC数据集可作为推动跨情境情绪识别研究、优化情绪解码方法实际应用的基础性科研资源。

搜集汇总

背景与挑战

背景概述

EmoEEG-MC是一个多上下文情感EEG数据集，包含60名参与者的64通道EEG和生理数据，覆盖视频诱导和想象诱导两种上下文下的七种情感类别。该数据集通过主观报告验证情感体验，旨在支持跨上下文情感识别研究，提升情感解码方法的实际应用能力。