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Emotions Detection based on a Single-electrode EEG Device

 

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Opened Access Emotions Detection based on a Single-electrode EEG Device
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Author: Quesada Tabares, Roylán
Molina Cantero, Alberto Jesús
Gómez González, Isabel María
Merino Monge, Manuel
Castro García, Juan Antonio
Cabrera Cabrera, Rafael
Department: Universidad de Sevilla. Departamento de Tecnología Electrónica
Date: 2017
Published in: PhyCS 2017: 4th International Conference on Physiological Computing Systems (2017), p 89-95
ISBN/ISSN: 978-989-758-268-4
Document type: Presentation
Abstract: The study of emotions using multiple channels of EEG represents a widespread practice in the field of research related to brain computer interfaces (Brain Computer Interfaces). To date, few studies have been reported in the literature with a reduced number of channels, which when used in the detection of emotions present results that are less accurate than the rest. To detect emotions using an EEG channel and the data obtained is useful for classifying emotions with an accuracy comparable to studies in which there is a high number of channels, is of particular interest in this research framework. This article uses the Neurosky Maindwave device; which has a single electrode to acquire the EEG signal, Matlab software and IBM SPSS Modeler; which process and classify the signals respectively. The accuracy obtained in the detection of emotions in relation to the economic resources of the hardware dedicated to the acquisition of EEG signal is remarkable.
Cite: Quesada Tabares, R., Molina Cantero, A.J., Gómez González, I.M., Merino Monge, M., Castro García, J.A. y Cabrera Cabrera, R. (2017). Emotions Detection based on a Single-electrode EEG Device. En PhyCS 2017: 4th International Conference on Physiological Computing Systems (89-95), Madrid, España: SciTePress.
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URI: https://hdl.handle.net/11441/77564

DOI: 10.5220/0006476300890095

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