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Emotion Recognition for hHman-Machine Communication | IEEE Conference Publication | IEEE Xplore

Emotion Recognition for hHman-Machine Communication


Abstract:

The ability to recognize emotion is one of the hallmarks of emotion intelligence. This paper proposed to recognize emotion using physiological signals obtained from multi...Show More

Abstract:

The ability to recognize emotion is one of the hallmarks of emotion intelligence. This paper proposed to recognize emotion using physiological signals obtained from multiple subjects. IAPS images were used to elicit target emotions. Five physiological signals: Blood volume pulse (BVP), Electromyography (EMG), Skin Conductance (SC), Skin Temperature (SKT) and Respiration (RESP) were selected to extract 30 features for recognition. Two pattern classification methods, Fisher discriminant and SVM method are used and compared for emotional state classification. The experimental results indicate that the proposed method provides very stable and successful emotional classification performance as 92% over six emotional states.
Date of Conference: 22-26 September 2008
Date Added to IEEE Xplore: 14 October 2008
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Conference Location: Nice, France

References

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