EEG Dataset for Emotion Analysis

Catalina Aguirre-Grisales (), Maria José Arbeláez-Arias, Andrés Felipe Valencia-Rincón, Hector Fabio Torres-Cardona and Jose Luis Rodriguéz-Sotelo
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Catalina Aguirre-Grisales: Department of Electronic Engineering, Faculty of Engineering, Universidad del Quindío, Armenia 16293, Colombia
Maria José Arbeláez-Arias: Department of Electronic Engineering, Faculty of Engineering, Universidad del Quindío, Armenia 16293, Colombia
Andrés Felipe Valencia-Rincón: Department of Electronic Engineering, Faculty of Engineering, Universidad del Quindío, Armenia 16293, Colombia
Hector Fabio Torres-Cardona: Department of Music, Faculty of Arts and Humanities, Universidad de Caldas, Manizales 170004, Colombia
Jose Luis Rodriguéz-Sotelo: Department of Electronic and Automation, Faculty of Engineering, Universidad Autónoma de Manizales, Manizalez 170001, Colombia

Data, 2025, vol. 10, issue 9, 1-18

Abstract: This work presents an EEG signal database derived from the induction of three emotional states using auditory stimuli. To this end, an experiment was designed in which 30 selected affective sounds from the IADS database were presented to 36 volunteers, from whom EEG signals were acquired. Stimuli were randomly configured in the Psychopy platform and synchronized via the LSL library with the OpenVibe signal acquisition platform. The 16-channel NautilusG brain computer interface was used for signal acquisition. As part of the database validation, a recognition system for the three emotional states was developed. This system utilized machine-learning-based parameterization and classification techniques, achieving detection percentages of 88.57%.

Keywords: EEG dataset; emotion analysis; brain–computer interface; emotion recognition patterns (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2025
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