Erkaymaz, HandeOzer, MahmutKaya, CerenOrak, I. Muharrem2024-09-292024-09-292015978-1-4673-7386-92165-0608https://hdl.handle.net/20.500.14619/842123nd Signal Processing and Communications Applications Conference (SIU) -- MAY 16-19, 2015 -- Inonu Univ, Malatya, TURKEYNowadays, artificial movements have been obtained by utilizing other organs for paralyzed patients. Especially the usage of eye movements for giving message to outside world became popular as a scientific subject. In studies according to eye movements, the Electrooculogram (EOG) signal is used. In this study, the vertical and horizontal FOG signals taken from electrodes, placed around the eyes, have been modelled by using Artificial Neural Networks (ANN) which is one of artificial intelligent technique. The system can sense four main directions (Right, Left, Up and Down) at the same time it can also detect blinking movements. Firstly, the signals have been pre-filtered, amplified and classified by ANN. The performance of recommended model has been demonstrated by analyzing statistical accuracy and confusion matrix according to the features of obtained signal. It has been seen that eye movements can be successfully determined by designed model.trinfo:eu-repo/semantics/closedAccessEOGPre-FilteringArtificial NetworkConfusion MatrixDirection DetectConference Object12311228WOS:000380500900287N/A