Emognition Wearable Dataset 2020

The Emognition dataset is dedicated to testing methods for emotion recognition (ER) from physiological responses and facial expressions. We collected data from 43 participants who watched short film clips eliciting nine discrete emotions: amusement, awe, enthusiasm, liking, surprise, anger, disgust, fear, and sadness. Three wearables were utilized to record physiological data: EEG, BVP (2x), HR, EDA, SKT, ACC (3x), and GYRO (2x), alongside the upper-body video recordings. After each film clip, participants completed two types of self-reports, i.e., related to nine discrete emotions and three dimensional ones: valence, arousal, motivation. The obtained data facilitates various ER approaches, e.g.,multimodal ER, EEG- vs. cardiovascular-based ER, discrete to dimensional representation transitions. The technical validation supported that watching film clips elicited the targeted emotions.Emognition数据集旨在测试基于生理反应与面部表情的情绪识别（emotion recognition, ER）方法。本研究招募43名受试者，令其观看可诱发九种离散情绪的短片片段，所诱发的情绪分别为：娱乐感、敬畏感、热情、喜爱、惊讶、愤怒、厌恶、恐惧与悲伤。研究采用三款可穿戴设备（wearables）采集生理数据，具体包括脑电图（electroencephalogram, EEG）、双路光电容积描记图（blood volume pulse, BVP，2路）、心率（heart rate, HR）、皮肤电活动（electrodermal activity, EDA）、皮肤温度（skin temperature, SKT）、三轴加速度计（accelerometer, ACC，3轴）与双路陀螺仪（gyroscope, GYRO，2路），同时同步采集受试者的上半身视频录像。每段短片播放完毕后，受试者需完成两类自评问卷：其一对应九种离散情绪，其二针对三维情绪维度，即效价（valence）、唤醒度（arousal）与动机性（motivation）。本数据集所获数据可为多种情绪识别研究方向提供支撑，例如多模态情绪识别、基于脑电图与基于心血管信号的情绪识别、离散情绪向维度情绪表征的转换等。经技术验证，观看指定短片可有效诱发预设的目标情绪。