EEG based brain-computer interface control applications: A comprehensive review

Abstract

Brain computer interfaces (BCI) is a tool that can make user requests to computerized systems by directly processing brain signals. In order to perform the procedures to be performed, brain signals must be classified. For this purpose, many classification algorithms have been tried with machine learning. The purpose of this study is to talk about both the type of brain signals used in the brain computer interface and the machine learning techniques used in the classification of these signals. In addition, summary information about the classification methods used in brain computer interface control applications in recent years are given in a table.