Classification of multi-channel EEG signals for migraine detection

Abstract

Migraine can only be detected by expert medical doctors. But recent studies showed that the migraine analysis can be done also by using EEG. These analyses are concerned with migraine diagnostic methods done by using EEG. T5-T3 channel of EEG was generally used in these proposed methods. However, the suitability of other channels in the diagnosis of migraine has not discussed. It is very important to find out which EEG channels and brain lobes are more important to learn the characteristics of migraine. The aim of this study is to analyze the each EEG channel separately for migraine patients. Analysis of this study is based on method in the literature that related to magnitude increase amount under flash stimulation. For this aim, beta band of each EEG channel's data were pre-processed by using Burg-AR method. Then these features were applied to a support vector machine (SVM) classifier to observe which channel is the more definitive. As a result of this study, it is proposed that T3, F7, O1 and O2 channels are the most decisive for diagnosis of migraine, based on PSD magnitude increase under flash stimulation. Also, which brain lobes are more affected from triggering factors of migraine attack is proposed. Furthermore, asymmetry feature of migraine is approved by EEG and alternative migraine diagnosis methods is proposed for future researches according to reaction type of physiological structure of scalp to flash stimulation.