Title :
EOG based intelligent direction detect system with pre-filtering algorithm
Author :
Erkaymaz, Hande ; Ozer, Mahmut ; Kaya, Ceren ; Orak, I. Muharrem
Author_Institution :
Bilgisayar Muhendisligi Bolumu, Bulent Ecevit Univ., Zonguldak, Turkey
Abstract :
Nowadays, 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 EOG 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.
Keywords :
artificial intelligence; electro-oculography; filtering theory; medical signal detection; neural nets; ANN; EOG-based intelligent direction detect system; artificial intelligent technique; artificial movements; artificial neural networks; blinking movement detection; confusion matrix; electrooculogram signal; eye movements; horizontal EOG signals; paralyzed patients; prefiltering algorithm; statistical accuracy; vertical EOG signals; Artificial neural networks; Electrooculography; Reactive power; Robots; Signal processing; Vehicles; Wheelchairs; Artificial Neural Network; Confusion Matrix; Direction Detect; EOG; Pre-Filtering;
Conference_Titel :
Signal Processing and Communications Applications Conference (SIU), 2015 23th
Conference_Location :
Malatya
DOI :
10.1109/SIU.2015.7130059