Türk, ÖmerÖzerdem, Mehmet Siraç2024-04-242024-04-242017Türk, Ö. ve Özerdem, M. S. (2017). Yerel ikili örüntü yöntemi kullanarak EEG kayıtlarından mental aktivite tespiti. IDAP 2017 - International Artificial Intelligence and Data Processing Symposium.9781538618806https://doi.org/10.1109/IDAP.2017.8090271https://hdl.handle.net/11468/235082017 International Artificial Intelligence and Data Processing Symposium, IDAP 2017 -- 16 September 2017 through 17 September 2017 -- -- 115012Electroencephalogram signals are widely used in the detection of different activities but not in the desired level. In this study with this motivation, it is aimed to obtain the attributes by using the Local Bilinear Pattern (LBP) method of EEG records for various mental activities and to classify these features by k-Nearest Neighbor (k-NN) method. The binary classification performance of these EEG records containing 5 mental tasks was evaluated. In addition, in order to evaluate classification performance, confusion matrix was used as model performance criterion. In the study, the average of the classification performance of all participants was found as 87.38%. As a model performance criterion from the participants' classification of mental activity, accuracy was 85.03%, precision was 85.40% and sensitivity was 85.47%. So, as a result the obtained results support the literature and the applicability of the LBP method for EEG markings has been confirmed.trinfo:eu-repo/semantics/closedAccessK-NnLocal binary patternMental activitiesConference Object2-s2.0-8503990724210.1109/IDAP.2017.8090271N/A