Title :
Negative emotion detection using EMG signal
Author :
Gouizi, Khadidja ; Maaoui, Choubeila ; Reguig, Fethi Bereksi
Author_Institution :
Dept. d´Electron. Biomed., Univ. Abou bekr Belkaid, Tlemcen, Algeria
Abstract :
Generally, Negative emotions can lead to health problems. In order to detect negative emotions, an advanced method of the EMG signal analysis is presented. Negative emotions of interest in this work are: fear, disgust and sadness. These emotions are induced with presentation of IAPS (International Affective Picture System) images. The EMG signal is chosen to extract a set of characteristic parameters to be used for classification of emotions. The analysis of EMG signal is performed using the wavelet transform technique to extract characteristic parameters while the classification is performed using the SVM (Separator Vector Machine) technique. The results show a good recognition rates using these characteristic parameters.
Keywords :
electromyography; emotion recognition; medical signal processing; signal classification; support vector machines; wavelet transforms; EMG signal analysis; IAPS images; International Affective Picture System images; SVM technique; emotion classification; health problems; negative emotion detection; separator vector machine technique; wavelet transform technique; Electromyography; Emotion recognition; EMG Signal; Negative emotions; Pertinents parameters; SVM Classifier; Wavelet transfrom;
Conference_Titel :
Control, Decision and Information Technologies (CoDIT), 2014 International Conference on
Conference_Location :
Metz
DOI :
10.1109/CoDIT.2014.6996980