Detecting depression using multimodal approach of emotion recognition

Abstract : Depression is a growing problem in our society. It causes pain and suffering not only to patients but also to those who care about them. This paper presents a multimodal emotion recognition system that is capable of preventing depression. It consists of detecting persistent negative emotions for early detection of depression. Our proposal is based on an algebraic representation of emotional states using multidimensional vectors. This algebraic model provides powerful mathematical tools for the analysis and the processing of emotions and permits the fusion of complementary information such as facial expression, voice, physiological signals, etc. Experiments results show the efficiency of the proposed method in detecting negative emotions by giving high recognition rate.
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Communication dans un congrès
IEEE. International conference on complex systems 2012, Nov 2012, Agadir, Morocco. <http://ieeexplore.ieee.org/document/6458534/>. <10.1109/ICoCS.2012.6458534>
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https://hal.archives-ouvertes.fr/hal-01516262
Contributeur : Nhan Le Thanh <>
Soumis le : samedi 29 avril 2017 - 18:16:43
Dernière modification le : dimanche 30 avril 2017 - 01:05:41

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Imen Tayari-Meftah, Nhan Le-Thanh, Chokri Ben-Amar. Detecting depression using multimodal approach of emotion recognition. IEEE. International conference on complex systems 2012, Nov 2012, Agadir, Morocco. <http://ieeexplore.ieee.org/document/6458534/>. <10.1109/ICoCS.2012.6458534>. <hal-01516262>

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