Affective computing
Toward Machine Emotional Intelligence: Analysis of Affective Physiological State
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
2005 Special Issue: A systems approach to appraisal mechanisms in emotion
Neural Networks - Special issue: Emotion and brain
2005 Special Issue: A systems approach to appraisal mechanisms in emotion
Neural Networks - Special issue: Emotion and brain
A survey of affect recognition methods: audio, visual and spontaneous expressions
Proceedings of the 9th international conference on Multimodal interfaces
Boredom, engagement and anxiety as indicators for adaptation to difficulty in games
Proceedings of the 12th international conference on Entertainment and media in the ubiquitous era
Emotion Recognition Based on Physiological Changes in Music Listening
IEEE Transactions on Pattern Analysis and Machine Intelligence
Asymmetric ratio and FCM based salient channel selection for human emotion detection using EEG
WSEAS Transactions on Signal Processing
Short-term emotion assessment in a recall paradigm
International Journal of Human-Computer Studies
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Computational Intelligence and Neuroscience - Neuromath: advanced methods for the estimation of human brain activity and connectivity
Affective computation on EEG correlates of emotion from musical and vocal stimuli
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Emotion assessment: arousal evaluation using EEG's and peripheral physiological signals
MRCS'06 Proceedings of the 2006 international conference on Multimedia Content Representation, Classification and Security
Experimental approach to affective interaction in games
Edutainment'06 Proceedings of the First international conference on Technologies for E-Learning and Digital Entertainment
A brain-computer interface to a plan-based narrative
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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In this paper, we describe our investigation of traces of naturally occurring emotions in electrical brain signals, that can be used to build interfaces that respond to our emotional state. This study confirms a number of known affective correlates in a realistic, uncontrolled environment for the emotions of valence (or pleasure), arousal and dominance: (1) a significant decrease in frontal power in the theta range is found for increasingly positive valence, (2) a significant frontal increase in power in the alpha range is associated with increasing emotional arousal, (3) a significant right posterior power increase in the delta range correlates with increasing arousal and (4) asymmetry in power in the lower alpha bands correlates with self-reported valence. Furthermore, asymmetry in the higher alpha bands correlates with self-reported dominance. These last two effects provide a simple measure for subjective feelings of pleasure and feelings of control.