Classification of EEG synchronization values of obsessive compulsive disorders patients using Support Vector Machine Method

Abstract

Obsessive Compulsive Disorders causes disruptive effect on brain oscillations. One of this disruptive effects is loss of synchronization. Global Field Synchronization indice that is calculated by Global Field Synchronization Method can detect degree of synchronization of EEG. According to analysis results, significantly difference was found between Global Field Synchronization Indice of OCD patients and healthy group in theta and delta frequency bands. For the purpose of testing success of GFS method in detecting OCD, GFS values of OCD patients and healthy group classified with Support Vector Machine method. In order to increase the performance of classification model, training and test data was selected by Cross Validation Method. Accuracy rate of classification results was found at 94.75 in delta band and 78.048 percent in theta band. The system can assist the physicians for diagnosing OCD. The classification results has shown that GFS is a successful method for to diagnose OCD.