Kendali Arah pada Brain Computer Interface Berbasis Steady State Visual Evoked Potentials

Abstract

Various studies regarding to Steady State Visual Evoked Potentials (SSVEP) based Brain Computer Interface (BCI) system with Electroencephalogram (EEG) signal has developed as BCI implementation on directional control, however lackness found on those studies which are long time on classification duration, to many electrode channels used and the electrode channels located on special area. This study we developed the SSVEP based BCI system with one second classification duration, four active channels used and electrode channels located based on The International 10-20 System. Stimulus used are red colored object with 11 Hz frequency rate represents as left directional control class, blue colored object with 13 Hz frequency rate represents as right directional control class and white colored background represents as relax class. Filter bank with eight frequency range (11 Hz, 22 Hz, 33 Hz, 13 Hz, 26 Hz, 39 Hz, 12-29 Hz dan 30-50 Hz) followed by Root Mean Square (RMS) used as feature extraction for every second of data. Artificial Neural Network (ANN) classification and 5-Fold Cross Validation are used to knowing the performance of the developed system. Developed BCI system resulted accuracy 78,20% with True Positive Rate (TPR) 86,00% and False Discovery Rate (FDR) 23,21%.