DOI: 10.5281/zenodo.8431450
title: EmoKey Moments Muse EEG Dataset (EKM-ED): A Comprehensive Collection of Muse S EEG Data and Key Emotional Moments

description: EmoKey Moments Muse EEG Dataset (EKM-ED): A Comprehensive Collection of Muse S EEG Data and Key Emotional Moments


 


Dataset Description:


The EmoKey Moments EEG Dataset (EKM-ED) is an intricately curated dataset amassed from 47 participants, detailing EEG responses as they engage with emotion-eliciting video clips. Covering a spectrum of emotions, this dataset holds immense value for those diving deep into human cognitive responses, psychological research, and emotion-based analyses.


Dataset Highlights:



	
Precise Timestamps: Capturing the exact millisecond of EEG data acquisition, ensuring unparalleled granularity.
	
Brainwave Metrics: Illuminating the variety of cognitive states through the prism of Delta, Theta, Alpha, Beta, and Gamma waves.
	
Motion Data: Encompassing the device's movement in three dimensions for enhanced contextuality.
	
Auxiliary Indicators: Key elements like the device's positioning, battery metrics, and user-specific actions are meticulously logged.
	
Consent and Ethics: The dataset respects and upholds privacy and ethical standards. Every participant provided informed consent. This endeavor has received the green light from the Ethics Committee at the University of Granada, documented under the reference: 2100/CEIH/2021.



A pivotal component of this dataset is its focus on "key moments" within the selected video clips, honing in on periods anticipated to evoke heightened emotional responses.


Curated Video Clips within Dataset:



	
		
			Film
			Emotion
			Duration (seconds)
		
	
	
		
			The Lover
			Baseline
			43
		
		
			American History X
			Anger
			106
		
		
			Cry Freedom
			Sadness
			166
		
		
			Alive
			Happiness
			310
		
		
			Scream
			Fear
			395
		
	



The cornerstone of EKM-ED is its innovative emphasis on these key moments, bringing to light the correlation between distinct cinematic events and specific EEG responses.


Key Emotional Moments in Dataset:



	
		
			Film
			Emotion
			Key moment timestamps (seconds)
		
	
	
		
			American History X
			Anger
			36, 57, 68
		
		
			Cry Freedom
			Sadness
			112, 132, 154
		
		
			Alive
			Happiness
			227, 270, 289
		
		
			Scream
			Fear
			23, 42, 79, 226, 279, 299, 334
		
	



Citation:
Gilman, T. L., et al. (2017). A film set for the elicitation of emotion in research. Behavior Research Methods, 49(6).
Link to the study


With its unparalleled depth and focus, the EmoKey Moments EEG Dataset aims to advance research in fields such as neuroscience, psychology, and affective computing, providing a comprehensive platform for understanding and analyzing human emotions through EEG data.


 


———————————————————————————————————
FOLDER STRUCTURE DESCRIPTION
———————————————————————————————————


- questionnaires: all there response questionnaires (Spanish); raw and preprocessed
Including SAM
|
——preprocessed: Ficha_Evaluacion_Participante_SAM_Refactored.csv: the SAM responses for every film clip



- key_moments: the key moment timestamps for every emotion’s clip


- muse_wearable_data: XXXX
|
|—raw
|——1: ID = 1 of subject
|————muse: EEG data of Muse device
|—————————ANGER_XXX.csv :  leg data of the anger elicitation
|—————————FEAR_XXX.csv :  leg data of the fear elicitation
|—————————HAPPINESS_XXX.csv :  leg data of the happiness elicitation
|—————————SADNESS_XXX.csv :  leg data of the sadness elicitation
|————order: film elicitation order of play: For example: HAPPINESS,SADNESS,ANGER,FEAR
…
|
|—preprocessed
|——unclean-signals: without removing EEG artifacts, noise, etc.
|————muse: EEG data of Muse device
|—————————0.0078125: data downsampled to 128 Hz from 256Hz recorded
|——clean-signals: removed EEG artifacts, noise, etc.
|————muse: EEG data of Muse device
|—————————0.0078125: data downsampled to 128 Hz from 256Hz recorded


The ethical consent for this dataset was provided by La Comisión de Ética en Investigación de la Universidad de Granada, as documented in the approval titled: 'DETECCIÓN AUTOMÁTICA DE LAS EMOCIONES BÁSICAS Y SU INFLUENCIA EN LA TOMA DE DECISIONES MEDIANTE WEARABLES Y MACHINE LEARNING' registered under 2100/CEIH/2021.