An Overview of Classification of Electrooculography (EOG) Signals by Machine Learning Methods - SUİÇMEZ, Alihan; TEPE, Cengiz; ODABAS, Mehmet Serhat (Gazi Universitesi Fen Bilimleri Dergisi Part C: Tasarim ve Teknoloji, 2022)
The distribution of the studies conducted between 2011-2021 in the fields of (Electrooculography) EOG and eye movements, EOG and wheelchair, EOG and eye angle, EOG and sleep state, EOG and mood estimation and EOG and game application was determined according to years, and the most cited studies were examined and presented. The study areas are listed as Eye Movement Classification, Wheelchair, Sleep state, Eye Angle, Mood State and Game Applications from the most to the least number of articles. When we examine in terms of the number of citations, they are listed as Sleeping state, Eye Movement Classification, Wheelchair, Eye Angle, Mood State and Game Applications, from the most to the least. In these studies, it has been tried to make the lives of people who have become disabled in various ways better by using the brain-computer interface with machine learning.
Keywords: Science (General); Science; Q; Mühendislik; Engineering (General). Civil engineering (General); eog; Q1-390; Engineering; machine learning; EOG; Electrooculography; Machine Learning; electrooculography; TA1-2040