Title :
Comparison of wavelets for classification of cognitive EEG signals
Author :
Eraldemir, S. Goksel ; Yildirim, Esen
Author_Institution :
Iskenderun Meslek Yuksekokulu, Mustafa Kemal Univ., Hatay, Turkey
Abstract :
In this work, different wavelet types, that have been frequently used in EEG signal analysis and classification, are compared for cognitive EEG classification. EEG signals are collected from 18 healthy subjects during math processing and simple text reading. Symlet, coiflet and bior wavelet types are used for feature extraction and classification performances of BayesNet and J48 classifiers are compared. The best true positive rate of 90.6% is obtained using Boir 2.4 wavelet type with J48 classifier.
Keywords :
cognition; discrete wavelet transforms; electroencephalography; feature extraction; medical signal processing; signal classification; BayesNet classifiers; Bior wavelet types; Coiflet wavelet types; EEG signal analysis; J48 classifiers; Symlet wavelet types; classification performances; cognitive EEG signal classification; discrete wavelet transform; feature extraction; math processing; text reading; Classification algorithms; Computer science; Discrete wavelet transforms; Electroencephalography; Wavelet analysis; Biorthogonal; Coiflet; Discrete Wavelet Transform; EEG Classification; Symlet;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location :
Malatya
DOI :
10.1109/SIU.2015.7130099