Çağatay Murat Yılmaz

Karadeniz Technical University · Department of Software Engineering

Non-invasive acquisition and analysis of human brain signals play a crucial role in the development of brain-computer interfaces, enabling their widespread applicability in daily life. Motor imagery has emerged as a prominent technique for the advancement of such interfaces. While initial machine and deep learning studies have shown promising resul...

Nowadays, motor imagery-based brain–computer interfaces (BCIs) have been developed rapidly. In these systems, electroencephalogram (EEG) signals are recorded when a subject is involved in the imagination of doing any motor imagery movement like the imagination of the right/left hands, etc. In this paper, we sought to validate and enhance our previo...

Eye state prediction is the process of determining whether the users' eyes are in opened or closed state. It has been widely employed in human computer interaction, braincomputer interfaces, etc. In this paper, we investigated the classification performances of different distance metrics and number of neighbour parameters on the problem of predicti...

Nowadays, EEG signals are highly used in the field of medical research, such as the treatment of epilepsy, and in the brain–computer interface systems. In this paper, our previously proposed Signal-to-Image Transformation (StIT) method is used for classification of EEG signals. StIT is a kind of finite transformation based on the detection of local...

The classification of magnetic signals has become one of the challenging research problems in brain computer interfaces (BCIs). Magnetic signals, as measured with electroencephalography (EEG) and magnetoencephalography (MEG), contain lots of additional information on the bioelectrical activity of the brain. In this paper, we propose a simple transf...

Background and objective: Electroencephalography (EEG) is a method that measures and records the electrical activity of the human brain. These biomedical signals are currently being actively used in many research fields and have a wide range of potential uses in brain-computer interfaces (BCIs). The main aim of the present work is to improve the...

Brain-computer interface (BCIs) is non-muscular communication and control system which allows users to send messages or control commands to any kind of electronic devices via neuronal activity patterns. Magnetoencephalography (MEG) has a rich source about functional, physiological and pathological status of the brain and has widely used to investig...

Eye state detection is the process of determining whether the eyes are opened or closed. It has been widely employed in driver fatigue/drowsiness detection, human computer interaction. However, there are still lots of problems remaining unsolved such as free head movements, changing pose and illumination. Due to this, a new appearance based method...

User's gaze on computer screen is widely being used in human computer interaction, virtual reality, computer game industry, usability tests, improving the quality of physically disabled people and drowsiness detection. In this work, gaze image data and computer screen are spatially mapped using appearance based video oculography methods. Furthermor...

Göz-bakışı izleme kullanıcının ekran üzerinde baktığı konumun ölçülmesidir. Özellikle insan bilgisayar etkileşimi alanında klavye ve fare gibi geleneksel giriş birimlerine alternatif olması amacıyla üzerinde sıkça çalışılmaktadır. Bu çalışmada gerçek zamanlı göz-bakış yönü tespiti için geliştirilen görüntü tabanlı sistem tanıtılmaktadır. Geliştiril...