Concentration Level Detection Using EEG Signal on Reading Practice Application

Learning concentration is an interesting topic to study. The concentration while a person study such as when he/she reading can be measured using electroencephalograph. Alpha wave is higher in the relaxation state while Beta wave is higher in the attention state. In this study, an application for reading practice has been developed. The application can be used to control page transition of text reader and also recording the electroencephalograph (EEG) of the user at the same time. In this study, the subject is asked read 3 paragraph and answer 4 question multiple choice test for each paragraph. While the subject reading the text, his/her EEG signal is recorded. The score that earned by the subject on each paragraph is then compared to the average EEG band power recorded while he/she read that particular paragraph. By using the alpha and beta wave, the score of the subject after he/she read the reading material is estimated. The Artificial Neural Network is used to develop the estimation model. There are four inputs that is used on this estimation model, namely low alpha power, high alpha power, low beta power, and high beta power. The result shows that the accuracy is 73.81% which can be categorized as reasonable.