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ThinkMind // GLOBAL HEALTH 2015, The Fourth International Conference on Global Health Challenges // View article global_health_2015_5_30_70133


Detection and Classification of the Basic Emotions Using a Multimodal Approach for Emotions Detection

Authors:
Chaka Koné
Cecile Belleudy
Imen Tayari Meftah
Nhan Le-Thanh

Keywords: Signal fusion method; basic emotions; multimodal detection; physiological signals

Abstract:
Negative emotions (anxiety, fear, anger, and grief) may affect physical health and the quality of life. Indeed, people with depression experience severe and prolonged feelings of negative emotions like sadness, anger, disgust and fear. On one hand, this paper presents a new method for the fusion of signals for the purpose of a multimodal recognition of eight basic emotions, on the other hand, it present a classification of these basic emotions in three emotional classes, namely, neutral, positive and negative emotions which are using physiological signals. After constructing an emotion data base during the learning phase, we apply the recognition algorithm on each modality separately. Then, we merge all these decisions separately by applying a decision fusion approach to improve recognition rate. The experiments show that the proposed method allows high accuracy emotion recognition. Indeed, we get a recognition rate of 81.69% under some conditions.

Pages: 84 to 89

Copyright: Copyright (c) IARIA, 2015

Publication date: July 19, 2015

Published in: conference

ISSN: 2308-4553

ISBN: 978-1-61208-424-4

Location: Nice, France

Dates: from July 19, 2015 to July 24, 2015

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