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Four-Channel Biosignal Analysis and Feature Extraction for Automatic Emotion Recognition

Jonghwa Kim and Elisabeth André

erschienen 2008 "Biomedical Engineering Systems and Technologies", Series "Communications in Computer and Information Science", Volume 25, Pages 265 - 277

Verlag: Springer


ISBN: 978-3-540-92219-3 DOI: DOI.org


Abstract:

This paper investigates the potential of physiological signals as a reliable channel for automatic recognition of user’s emotial state. For the emotion recognition, little attention has been paid so far to physiological signals compared to audio-visual emotion channels such as facial expression or speech. All essential stages of automatic recognition system using biosignals are discussed, from recording physiological dataset up to feature-based multiclass classification. Four-channel biosensors are used to measure electromyogram, electrocardiogram, skin conductivity and respiration changes. A wide range of physiological features from various analysis domains, including time/frequency, entropy, geometric analysis, subband spectra, multiscale entropy, etc., is proposed in order to search the best emotion-relevant features and to correlate them with emotional states. The best features extracted are specified in detail and their effectiveness is proven by emotion recognition results.


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