EEG Features Extraction for Classification of Human Intention and Non-Intention - Phan, Duy Hung; Vu, Minh Thang; Vu, Thu Diep (Old Journal, 2017)
This study is to classify brain's state Intention and Non-Intention base on only one channel of the Electroencephalogram (EEG) signal, then apply results to real world's problem. Because the brain signal is much different between different people, this article only discusses personal EEG data. First, data is recorded by EEG-SMT device of Olimex Ltd. Then we extracted features from collected EEG data and used the ANOVA tool to evaluate significant of them. Multilayer Neutral Network is used for the training process. The accuracy is normally above 90% for each subject by using proposed features. Finally, a method of smoothing real-time results is developed to improve training results and to play simple computer games.