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
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;
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
DOI :
10.1109/SSD.2013.6564011
