EEG-Based Emotion Recognition: A State-of-the-Art Review of Current Trends and Opportunities

Table 3

Publicly available datasets for emotion stimulus and emotion recognition with different methods of collection for neurophysiological signals.

Item No.	Dataset	Description
1	DEAP	“Dataset for Emotion Analysis using Physiological and Video Signals” is an open-source dataset to analyze human affective states. The dataset consists of 32 recorded participants watching 40 music video clips with a certain level of stimuli evaluated
2	IADS	“The International Affective Digital Sounds” system is a collection of digital sounds that is used to stimulate emotional responses through acoustics and is used in investigations of emotion and attention of an individual
	IAPS	“The International Affective Picture” system is a collection of the emotionally evocative picture that is used to stimulate emotional responses to investigate the emotion and attention of an individual
4	DREAMER	A dataset that has collected 23 participants with signals from EEG and ECG using audio-visual stimuli responses. The access of this dataset is restricted and can be requested upon filling a request form to the owner
5	ASCERTAIN	A “database for implicit personality and affect recognition” that collects signals from EEG, ECG, GSR, and facial activities from 58 individuals using 36 movie clips with an average length of 80 seconds
6	SEED	The “SJTU Emotion EEG Dataset” is a collection of EEG signals collected from 15 individuals watching 15 movie clips and measures the positive, negative, and neutral emotions
7	SEED-IV	An extension of the SEED dataset that now specifically targets the labels of the emotion specifically, happy, sad, fear, and neutral with an additional eye tracking feature added into the collection data inclusive of the EEG signal