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Eye Movement Classification via EOG by Luthfi Achmad Fadhil is a document available to read on EtoBox.
What is Eye Movement Classification via EOG about?
This document presents a study on classifying eleven eye movements using electrooculography and neural networks. Electrooculography measures eye movements by detecting the cornea-retinal potential. The study uses signal processing and time delay neural networks to process raw EOG signals and identify eye movements. Simple feature extraction algorithms are proposed based on Parseval and Plancherel theorems. The time delay neural network classifiers achieved an average accuracy of 91.40% and 90.89% respective
- Author
- Luthfi Achmad Fadhil
- Language
- EN