Eye State Prediction Based on EEG Signal Data Neural Network and Evolutionary Algorithm Optimization - Untari Novia Wisesty; Hifzi Priabdi; Rita Rismala; Mahmud Dwi Sulistiyo (Indonesia Journal on Computing (Indo-JC), 2020)
Eye state prediction is one study using EEG signals obtained to predict the state of the human eye several moments before. In its development, many researchers also have built eye states detection schemes, but the system built is only limited to classifying one record of input data obtained from the Emotive EPOC headset channel into the eye state. Therefore, this paper proposed eye state prediction system where the system can predict the state of the human eye some time previously based on the EEG signal series used. The proposed system consists of two parts, namely the prediction of the EEG signal value and eye state detection based on the value of the signal that has been obtained using Differential Evolution and Neural Network optimized by Evolution Strategies, respectively. The highest accuracy obtained from the eye state prediction system that has been built is 73.2%. These results are obtained by the best combination of parameters from the three methods used.