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Öğe Classification of Simple Text Reading and Mathematical Tasks from EEG(Ieee, 2014) Eraldemir, S. Goksel; Yildirim, EsenAll types of brain activity produce electrical signals. These signals emerge during body movement, as well as at the stage of thinking and they can be recorded using an EEG device. In this study EEG signals of healthy volunteers were recorded during simple mathematical tasks and text reading. The aim of the study is to discriminate these activities from recorded EEG signals. For this purpose we used EEG signals recorded from healthy volunteers using international 10-20 electrode placing system. Features are extracted using wavelet transform and they used for classification using Bayesian Classifiers. As a result of the study EEG signals, recorded during mathematical operations and text reading, were classified with a true positive rate of 89.1% and a precision rate of 89.2% on the average.Öğe Comparison of Wavelets for Classification of Cognitive EEG Signals(Ieee, 2015) Eraldemir, S. Goksel; Yildirim, EsenIn 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.