Classify Mental States from EEG Signal Using Xgboost Algorithm

Brain-computer interface (BCI) is a leading edge technique which allows the brain communicates with external devices. It has been applied in several fields, such as medical rehabilitation, virtual reality and so on. This invention introduces a technique that can be applied in education field to monitor and analyze users' electroencephalogram (EEG) so that the mental states could be identified. The algorithm of classifier used XGBoost which combined Bayes, KNN and SVM in it and its accuracy could reach to 80%. By using this technique, teacher could obtain the concentration status of students in real time and adjust his or her teaching method or remind the student who is wandering. Data collection Import data Feature Absolute Mean Variance coPeaatn PeaSkew extraction E Data pre-processing Visualization Classifier ayes ANN XGBoost Fine-tuning Result analysisI Figure 1