title: EEG Responses to Auditory Stimuli for Automatic Affect Recognition.
abstract: Brain state classification for communication and control has been well established in the area of brain-computer interfaces over the last decades. Recently, the passive and automatic extraction of additional information regarding the psychological state of users from neurophysiological signals has gained increased attention in the interdisciplinary field of affective computing. We investigated how well specific emotional reactions, induced by auditory stimuli, can be detected in EEG recordings. We introduce an auditory emotion induction paradigm based on the International Affective Digitized Sounds 2nd Edition (IADS-2) database also suitable for disabled individuals. Stimuli are grouped in three valence categories: unpleasant, neutral, and pleasant. Significant differences in time domain domain event-related potentials are found in the electroencephalogram (EEG) between unpleasant and neutral, as well as pleasant and neutral conditions over midline electrodes. Time domain data were classified in three binary classification problems using a linear support vector machine (SVM) classifier. We discuss three classification performance measures in the context of affective computing and outline some strategies for conducting and reporting affect classification studies.
authors.affiliation: Developmental Aspects of Sleep, Memory, and Emotion, Institute of Medical Psychology and Behavioural Neurobiology, University of TübingenTübingen, Germany; Neural Interfaces and Brain Signal Decoding, Wilhelm-Schickard-Institute for Computer Science, University of TübingenTübingen, Germany.
authors.forename: Dirk T
authors.initials: DT
authors.lastname: Hettich
authors.affiliation: Developmental Aspects of Sleep, Memory, and Emotion, Institute of Medical Psychology and Behavioural Neurobiology, University of Tübingen Tübingen, Germany.
authors.forename: Elaina
authors.initials: E
authors.lastname: Bolinger
authors.affiliation: Developmental Aspects of Sleep, Memory, and Emotion, Institute of Medical Psychology and Behavioural Neurobiology, University of Tübingen Tübingen, Germany.
authors.forename: Tamara
authors.initials: T
authors.lastname: Matuz
authors.affiliation: Developmental Aspects of Sleep, Memory, and Emotion, Institute of Medical Psychology and Behavioural Neurobiology, University of TübingenTübingen, Germany; Ospedale San Camillo, IRCCSVenezia, Italy.
authors.forename: Niels
authors.initials: N
authors.lastname: Birbaumer
authors.affiliation: Neural Interfaces and Brain Signal Decoding, Wilhelm-Schickard-Institute for Computer Science, University of Tübingen Tübingen, Germany.
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Rosenstiel
authors.affiliation: Neural Interfaces and Brain Signal Decoding, Wilhelm-Schickard-Institute for Computer Science, University of Tübingen Tübingen, Germany.
authors.forename: Martin
authors.initials: M
authors.lastname: Spüler
keywords: affective computing; brain-computer interface; classification; event-related potential; late positive potential; machine learning; support vector machine