Research Information System
SAKARYA UNIVERSITY JOURNAL OF SCIENCE, vol.28, no.6, pp.1146-1157, 2024 (Scopus, TRDizin)
Virtual Reality (VR) systems have become widespread for a decade with
the mass production of VR headsets. Advancement in the VR industry
benefits both biomedical and computer gaming fields to create better
Human-Computer Interface (HCI) applications. In this study,
Electrooculogram (EOG) signals are studied on a calibrated A4 paper to
simulate reading and tracking eye movement in different regions for VR
user interface applications. For that reason, eye activity features from
EOG are used to identify relative 2D spatial coordinates and classified
with the fuzzy k-Nearest Neighbor (fuzzy k-NN) method. Within the
experimental setup, different behaviors such as blinking and depth focus
change signals are recorded with constant depth regional borders are
analyzed on an A4 paper with reading eye movement recordings. In
experimental results, fuzzy k-NN classification results are obtained
from observed regional eye movement. The study shows that the fuzzy k-NN
method to detect regions at a reading distance is feasible for user
interface applications in VR. So, by setting rendering focus at the
detected regional area, eye strain can be reduced during prolonged VR
sessions especially when reading and/or on user interfaces.