DocumentCode
1781789
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
fYear
2014
fDate
3-5 Nov. 2014
Firstpage
690
Lastpage
695
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Control, Decision and Information Technologies (CoDIT), 2014 International Conference on
Conference_Location
Metz
Type
conf
DOI
10.1109/CoDIT.2014.6996980
Filename
6996980
Link To Document