Emotion recognition based on physiological changes in music listening

• Published in: IEEE transactions on pattern analysis and machine intelligence Vol. 30; no. 12; pp. 2067 - 2083
• Main Authors: Jonghwa Kim, Andre, Elisabeth
• Format: Journal Article
• Language: English
• Published: Los Alamitos, CA IEEE 01.12.2008; IEEE Computer Society; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation, Physiological - physiology; Algorithms; and processing; Applied sciences; Arousal; Arousal - physiology; Artificial Intelligence; Auditory Perception - physiology; Biosensors; Channels; Classification; Classifier design and evaluation; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Conductivity measurement; Discriminant analysis; Disk recording; Emotion recognition; Emotions; Emotions - physiology; Entropy; Exact sciences and technology; Feature evaluation and selection; Frequency; Human-centered computing; Humans; Intelligence; Interaction styles; Laboratories; Methodologies and techniques; Monitoring, Physiologic - methods; Music; Pattern analysis; Pattern Recognition, Automated - methods; Pattern recognition. Digital image processing. Computational geometry; Recognition; Robotics; Signal analysis; Signal processing; Skin; Software; Speech; Studies; synthesis; Theory and methods; User/Machine Systems; synthesis; and processing; Human-centered computing; Feature evaluation and selection; User/Machine Systems; Theory and methods; Classifier design and evaluation; Robotics; Signal processing; Methodologies and techniques; Interaction styles; Signal analysis; Pattern analysis; Autonomous system; Time frequency domain method; Man machine system; affective computing; respiration; Modeling; electromyogram; Audiovisual; Induction method; electrocardiogram; User interface; Musical acoustics; Classification; Facies; Electrocardiography; Audiovisual equipment; Time analysis; Pattern extraction; physiological signal; Emotion recognition; Discriminant analysis; autonomic nervous system; skin conductance; biosignal; Frequency domain method; Emotion emotionality; valence; human-computer interaction; Multiscale method; Biosensor; Music; musical emotion; Skin; Automatic recognition; Artificial intelligence; Multiclass; Facial expression; arousal

Little attention has been paid so far to physiological signals for emotion recognition compared to audiovisual emotion channels such as facial expression or speech. This paper investigates the potential of physiological signals as reliable channels for emotion recognition. All essential stages of an...