Bülbül, Emre
The standard method for assessing a patient’s visual field is visual field testing. Many diseases, including glaucoma, which affects more than 80 million people, require visual field testing for monitoring and diagnosis. The testing is done by sending light to fixed locations with different luminosities while the patient is fixating at a certain point, then the sensitivities to light at each location are determined by recording the responses of the patient to seen stimuli. Because of their form and digital screens, virtual reality headsets have lately begun to be utilized to conduct visual field examinations. However, since the testing duration is long, it causes fatigue in patients, which decreases cooperation and test accuracy. Also, it limits how many tests a clinic can conduct in a day. In this thesis, using a digital screen, the number of testable point locations is increased, and the effect of using an optimal subset of locations, which is found by employing a reinforcement learning method to decrease test duration, is investigated. Also, the effect of using forecasted future visual field test results in testing to the test duration is compared with standard testing strategies.


The Effect of Virtual Reality and Prediction in Visual Field Test Görme Alani Testinde Sanal Gerçeklik ve Öngörmenin Etkisi
Bulbul, Emre; Akar, Gözde (2022-01-01)
© 2022 IEEE.Visual field testing is the gold standard for evaluating a patient's visual field. Visual field testing is required for monitoring and diagnosis of several disorders, including glaucoma, which affects more than 80 million individuals. While the patient is fixated at a certain place, light of various luminosities is sent to fixed locations, and the sensitivities to light at each position are calculated by recording the patient's responses to observed stimuli. Virtual reality headsets have just be...
Multi-time-scale input approaches for hourly-scale rainfall-runoff modeling based on recurrent neural networks
Ishida, Kei; Kiyama, Masato; Ercan, Ali; Amagasaki, Motoki; Tu, Tongbi (2021-11-01)
This study proposes two effective approaches to reduce the required computational time of the training process for time-series modeling through a recurrent neural network (RNN) using multi-time-scale time-series data as input. One approach provides coarse and fine temporal resolutions of the input time-series data to RNN in parallel. The other concatenates the coarse and fine temporal resolutions of the input time-series data over time before considering them as the input to RNN. In both approaches, first, ...
Quantitative measurements obtained by micro-computed tomography and confocal laser scanning microscopy
KAMBUROĞLU, KIVANÇ; Barenboim, S. F.; Arituerk, T.; Kaffe, I. (British Institute of Radiology, 2008-10-01)
Objectives: To compare measurements obtained by micro-CT with those obtained by confocal laser scanning microscope in simulative internal resorption cavities.
Experimental results on adaptive output feedback control using a laboratory model helicopter
Kutay, Ali Türker; Idan, Moshe; Hovakimyan, Naira (2002-01-01)
Experimental results are presented that illustrate a recently developed method for direct output feedback adaptive control. The method permits adaptation to both parametric uncertainty and unmodeled dynamics, and incorporates a novel approach that permits adaptation during periods of control saturation. A controller designed using this method was tested in controlling the pitch axis of a three degrees of freedom helicopter model, using attitude feedback through a low resolution optical sensor. © 2002 by the...
Evaluation of UAS Camera Operator Interfaces in a Simulated Task Environment An Optical Brain Imaging Approach
Çakır, Murat Perit; Akay, Daryal; Ayaz, Hasan; İşler, Veysi (null; 2012-07-11)
In this paper we focus on the effect of different interface designs on the performance and cognitive workload of sensor operators (SO) during a target detection task in a simulated environment. Functional near-infrared (fNIR) spectroscopy is used to investigate whether there is a relationship between target detection performance across three SO interfaces and brain activation data obtained from the subjects’ prefrontal cortices that are associated with relevant higher-order cognitive functions such as atten...
Citation Formats
E. Bülbül, “VISUAL FIELD TESTING USING FORECASTING AND VIRTUAL REALITY,” M.S. - Master of Science, Middle East Technical University, 2022.