A5042577715- EEG and Brain-Computer Interfaces
- ECG Monitoring and Analysis
- Non-Invasive Vital Sign Monitoring
- Cardiovascular Health and Disease Prevention
- Gaze Tracking and Assistive Technology
- Blind Source Separation Techniques
- Heart Rate Variability and Autonomic Control
- Advanced Adaptive Filtering Techniques
- AI in cancer detection
- Functional Brain Connectivity Studies
- Muscle activation and electromyography studies
- Neural Networks and Applications
- Neural dynamics and brain function
- Tactile and Sensory Interactions
- Artificial Immune Systems Applications
- Digital Imaging for Blood Diseases
- Ultrasound Imaging and Elastography
- Neurological disorders and treatments
- Artificial Intelligence in Healthcare
- Retinal Imaging and Analysis
- Image and Signal Denoising Methods
- Atherosclerosis and Cardiovascular Diseases
- Cardiac Arrest and Resuscitation
- Fractal and DNA sequence analysis
- Parkinson's Disease Mechanisms and Treatments
Erciyes University
2015-2025
Bozok Universitesi
2021-2023
Afyon Kocatepe University
2020
Kayser (Italy)
2007-2017
Bridge University
2016
Kayseri Eğitim ve Araştırma Hastanesi
2006
Complexity measures have been enormously used in schizophrenia patients to estimate brain dynamics. However, the conflicting results terms of both increased and reduced complexity values reported these studies depending on patients' clinical status or symptom severity medication age status. The objective this study is investigate nonlinear dynamics chronic medicated using distinct estimators. EEG data were collected from 22 relaxed eyes-closed age-matched healthy controls. A single-trial...
Objective.Attention deficit hyperactivity disorder (ADHD) is considered one of the most common psychiatric disorders in childhood. The incidence this disease community draws an increasing graph from past to present. While ADHD diagnosis basically made with tests, there no active clinically used objective diagnostic tool. However, some studies literature has reported development tool that facilitates ADHD.Approach.In study, it was aimed develop for using electroencephalography (EEG) signals....
This study aimed to evaluate the effect of maternal vitamin D use during intrauterine life on fetal bone development using ultrasonographic image processing techniques. We evaluated 52 pregnant women receiving supplementation and 50 who refused supplementation. Ultrasonographic imaging was performed clavicle at 37-40 weeks gestation. The images were compared with adult male images. texture features obtained from these used for analysis. No difference observed in formation destruction markers...
Cisplatin, a widely used chemotherapeutic agent, is highly effective in treating various cancers, including ovarian and lung but it often causes tissue damage impairs reproductive health. Exosomes derived from mesenchymal stem cells are believed to possess reparative effects on such damage, as suggested by previous studies. This study aims evaluate the of cisplatin exosome treatments through analysis histopathological images machine learning (ML)-based classification techniques. Five...
Abstract Parkinson’s disease (PD) is the second most common neurological disorder caused by damage to dopaminergic neurons. Therefore, it important develop systems for early and automatic diagnosis of PD. For this purpose, a study that will contribute development PD presented. The Electroencephalography (EEG) signals were decomposed into sub-bands using adaptive decomposition methods, such as empirical mode decomposition, variational Vold-Kalman order filtering (VKF). Various features...
This study proposes a novel method that uses electroencephalography (EEG) signals to classify Parkinson's Disease (PD) and demographically matched healthy control groups. The utilizes the reduced beta activity amplitude decrease in EEG are associated with PD. involved 61 PD patients controls groups, were recorded various conditions (eyes closed, eyes open, both open on-drug, off-drug) from three publicly available data sources (New Mexico, Iowa, Turku). preprocessed classified using features...
In contemporary medicine, the development of computer-aided diagnostic systems using Electrocardiography (ECG) signals has gained significance for diagnosis heart diseases. Myocardial infarction (MI) is recognized as condition where blood flow to muscle obstructed due blockages in coronary vessels. this study, four deep learning approaches were employed automatically identify different MI conditions (STEMI, NSTEMI, USAP) images generated from 12-lead ECG signals. The utilized architectures...
In recent years, some electrophysiological analysis methods of consciousness have been proposed. Most these studies are based on visual interpretation or statistical analysis, and there is hardly any work classifying the level in a deep coma. this study, we perform an electroencephalography complexity measures by quantifying features efficiency differentiating patients different levels. Several proposed to quantify signals. Our aim lay foundation system that will objectively define...
In this paper, it is aimed to analysis of Electrooculography (EOG) signals recorded during the back eye movement (retrieving words/re-reading) and skipping lines while reading. Two situations are characterized by large amplitude fluctuations in EOG signals. For aim, were simultaneously reading a text from 10 volunteers changes caused jumping bottom line movements as analyzed. The classification these may allow development new method for early rapid diagnosis various disorders (for example...
Due to the fact that there exist only a small number of complex systems in artificial immune (AISs) solve nonlinear problems, is need develop AIS approaches would be among well-known solution methods. In this study, we developed kernel-based compensate for deficiency by providing structure via transformation distance calculations clonal selection models classical kernel space. Applications system were conducted on Statlog heart disease dataset, which was taken from University California,...
A system based on objective data was developed in the diagnosis and follow-up of attention-deficit hyperactivity disorder (ADHD) this study. First all, an electronic circuit, with a two-channel instrumentation amplifier designed to detect eye movements horizontal vertical directions via surface electrodes, obtain electrooculogram (EOG) signals. In order provide controlled analysis during reception signal, attention test visual stimulus software developed. Eight patients ADHD eight healthy...