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Emotion Detection Using Physiological Signals | IEEE Conference Publication | IEEE Xplore

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The two-dimensional Russell's model categorizes emotions into four classes. The positive and negative ratings of the emotions specify the valence levels in the expressed emotions. The intensity levels in the emotions direct the arousal. Happiness indicates high arousal & high valence (HAHA). Emotion such as Anger reveals low valence & high arousal levels(LVHA). The sadness demonstrates low valence & low arousal (LVLA), and the relaxed state specifies high valence & low arousal(HVLA). Emotions are detected using various biosignals such as Electrocardiogram (ECG), respiratory signals, Blood volume pulse (BVP), Electrodermal Activity(EDA)[1]. Emotion recognition using smart wearables has become popular due to its ease and reliability in emotion detection in the natural context of participants. The baseline of the ECG signal represents no overall depolarization or repolarization. The QRS complex is an indication of ventricular depolarization. The interbeat intervals of the ECG signals enab

I. Introduction The two-dimensional Russell's model categorizes emotions into four classes. The positive and negative ratings of the emotions specify the valence levels in the expressed emotions. The intensity levels in the emotions direct the arousal. Happiness indicates high arousal & high valence (HAHA). Emotion such as Anger reveals low valence & high arousal levels(LVHA). The sadness demonstrates low valence & low arousal (LVLA), and the relaxed state specifies high valence & low arousal(HVLA). Emotions are detected using various biosignals such as Electrocardiogram (ECG), respiratory…

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