Title :
Support vector EEG classification in the Fourier and time-frequency correlation domains
Author :
Garcia, Gary N. ; Ebrahimi, Touradj ; Vesin, Jean-Marc
Author_Institution :
EPFL, Swiss Fed. Inst. of Technol., Lausanne, Switzerland
Abstract :
We use support vector machines (SVM) for classifying EEG signals corresponding to imagined motor movements. The parameters of an SVM Kernel are optimized for minimizing a theoretical error bound. Fourier features and correlative time-frequency based features are extracted from EEG signals and compared with respect to their discriminatory power.
Keywords :
electroencephalography; feature extraction; medical signal processing; pattern classification; support vector machines; EEG signals; Fourier features; SVM Kernel; correlative time-frequency based features; direct brain-computer communication; discriminatory power; imagined motor movements; support vector EEG classification; support vector machines; theoretical error bound; Electrodes; Electroencephalography; Feature extraction; Kernel; Scalp; Signal analysis; Signal processing; Support vector machine classification; Support vector machines; Time frequency analysis;
Conference_Titel :
Neural Engineering, 2003. Conference Proceedings. First International IEEE EMBS Conference on
Print_ISBN :
0-7803-7579-3
DOI :
10.1109/CNE.2003.1196897
