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.