DocumentCode
621953
Title
EEG classification using support vector machine
Author
Ines, Homri ; Slim, Yacoub ; Noureddine, Ellouze
Author_Institution
Lab. Signal Image et Technol. de l´Inf., Univ. Tunis El Manar, Tunis, Tunisia
fYear
2013
fDate
18-21 March 2013
Firstpage
1
Lastpage
4
Abstract
EEG data of motor imagery of left and right hand movement are analyzed; different wavelet functions are applied to EEG segments for features extraction. Support vector machine is utilized for right and left hand movement imagination classification, than, the obtained results are compared with neural networks and linear discriminant analysis classification results.
Keywords
electroencephalography; feature extraction; medical signal processing; signal classification; support vector machines; wavelet transforms; EEG motor imagery data classification; EEG segments; feature extraction; left-hand movement imagination classification; right-hand movement imagination classification; support vector machine; wavelet functions; Accuracy; Brain modeling; Electroencephalography; Feature extraction; Image segmentation; Support vector machines; Wavelet analysis; EEG; Wavelet function; support vector machine;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Signals & Devices (SSD), 2013 10th International Multi-Conference on
Conference_Location
Hammamet
Print_ISBN
978-1-4673-6459-1
Electronic_ISBN
978-1-4673-6458-4
Type
conf
DOI
10.1109/SSD.2013.6564011
Filename
6564011
Link To Document