Publication | Closed Access
Analysis physiological signals for emotion recognition
33
Citations
1
References
2011
Year
Unknown Venue
EngineeringAffective DesignBiometricsAffective NeuroscienceWearable TechnologyMultimodal Sentiment AnalysisPsychologySocial SciencesEmotional ResponsePattern RecognitionPsychophysiologyAffective ComputingSupport Vector MachinesCognitive ScienceAnalysis Physiological SignalsFacial Expression RecognitionEmotions RecognitionEmotionEmotion Recognition
The emotion recognition is one of the great challenges in human-human and human-computer interaction. In this paper, an approach for the emotions recognition based on physiological signals is proposed. Six basic emotions: joy, sadness, fear, disgust, neutrality and amusement are analysed using physiological signals. These emotions are induced through the presentation of IAPS pictures (International Affecting Picture System) to the subjects. Also, the physiological signals of interest in this analysis are: electromyogram signal (EMG), respiratory volume (RV), skin temperature (SKT), skin conductance (SKC), blood volume pulse (BVP) and heart rate (HR). These are selected to extract some characteristic parameters, which will be used for classifying the emotions. The SVM (support vector machines) technique is used for classifying these parameters. The experimental results show that the proposed methodology provides a recognition rate of 85% for different emotional states.
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