Authors
Johannes Wagner, Jonghwa Kim, Elisabeth André
Publication date
2005/7/6
Conference
2005 IEEE international conference on multimedia and expo
Pages
940-943
Publisher
IEEE
Description
Little attention has been paid so far to physiological signals for emotion recognition compared to audio-visual emotion channels, such as facial expressions or speech. In this paper, we discuss the most important stages of a fully implemented emotion recognition system including data analysis and classification. For collecting physiological signals in different affective states, we used a music induction method which elicits natural emotional reactions from the subject. Four-channel biosensors are used to obtain electromyogram, electrocardiogram, skin conductivity and respiration changes. After calculating a sufficient amount of features from the raw signals, several feature selection/reduction methods are tested to extract a new feature set consisting of the most significant features for improving classification performance. Three well-known classifiers, linear discriminant function, k-nearest neighbour and multilayer …
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Scholar articles
J Wagner, J Kim, E André - 2005 IEEE international conference on multimedia and …, 2005