Mimoun Ben Henia Wiem

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Emotion recognition from physiological signals attracted the attention of researchers from different disciplines, such as affective computing, cognitive science and psychology. This paper aims to classify emotional statements using peripheral physiological signals based on arousal-valence evaluation. These signals are the Electrocardiogram, Respiration(More)
Emotion recognition becomes an investigated topic in affective computing for several applications. The presented paper aims to recognize human emotions using peripheral physiological signals as well as electrocardiogram (ECG), galvanic skin response (GSR), Skin Temperature (Temp) and respiration volume (RV). To achieve this purpose, we develop our work with(More)
This paper aims to recognize the human emotional states into three defined areas in arousal-valence evaluation: Corresponding to calm, medium aroused, and excited, unpleasant, neutral valence and pleasant. And thanks to the relevance of the peripheral physiological signals in emotion recognition issue, we used in our contribution the multimodal dataset(More)
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