A5007215914- EEG and Brain-Computer Interfaces
- ECG Monitoring and Analysis
- Non-Invasive Vital Sign Monitoring
- Neurological disorders and treatments
- Neuroscience and Neural Engineering
- Muscle activation and electromyography studies
- Functional Brain Connectivity Studies
- Vestibular and auditory disorders
- COVID-19 diagnosis using AI
- Fault Detection and Control Systems
- Anomaly Detection Techniques and Applications
- Machine Fault Diagnosis Techniques
- Artificial Intelligence in Healthcare
- Blind Source Separation Techniques
- Migraine and Headache Studies
- Hand Gesture Recognition Systems
- Parkinson's Disease Mechanisms and Treatments
- Wireless Body Area Networks
- Gaze Tracking and Assistive Technology
- Digital Imaging for Blood Diseases
- Tactile and Sensory Interactions
Inonu University
2020-2024
Erciyes University
2021-2022
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...
Migraine is a neurological disorder that associated with severe headaches and seriously affects the lives of patients. Diagnosing Disease (MD) can be laborious time-consuming for specialists. For this reason, systems assist specialists in early diagnosis MD are important. Although migraine one most common diseases, there very few studies on MD, especially electroencephalogram (EEG)-and deep learning (DL)-based studies. study, new system has been proposed EEG- DL-based MD. In EEG signals...
Mental workload (MWL) can be estimated according to the state of cognitive capacity after an activity. In this study, it is aimed classify MWL levels from Electroencephalogram (EEG) signals recorded a task moment. Using proposed one-dimensional convolutional neural network (1D-CNN) model in low (L) and high (H) level WL states were classified. The classification process was carried out two stages. EEG passed through preprocessing stage classified with 1D-CNN first stage. second step, these...
This study, it was aimed to contribute the literature on Amyotrophic lateral sclerosis (ALS) diagnosis and Brain-Computer Interface (BCI) technologies by analyzing electroencephalography (EEG) signals obtained as a result of visual stimuli attention from ALS patients healthy controls. It observed that success rate significantly increased both in occipital central regions all classifiers, especially entropy features. The most successful classification with Naïve Bayes (NB) classifier using...
Amyotrophic lateral sclerosis (ALS), also known as motor neuron disease, is a neurological disease that occurs result of damage to the nerves in brain and restriction muscle movements. Electroencephalography (EEG) most common method used imaging study disorders. Diagnosis disorders such ALS, Parkinson's, attention deficit hyperactivity disorder important biomedical studies. In recent years, deep learning (DL) models have been started be applied literature for diagnosis these diseases. this...
Farklı nörolojik hastalıkların neden olduğu beyinde oluşan anormal durumlar dünya çapında birçok insanı etkilemektedir. Bu durumlardan birisi de Amyotrofik lateral skleroz (ALS)'dur. ALS, beyin sapı adı verilen bölgede motor sinir hücrelerinin zarar görmesiyle ilerleyen fiziksel bozukluklara olan genellikle nöron hastalığı olarak bilinen bir hastalıktır. Beyin, dışarıdan gelen uyarıları algılar ve algılanan çok sayıda uyarıdan ilgili olanları dikkat mekanizması sayesinde seçer. Dikkat,...
Şizofreni (SZ), dünya çapında birçok insanı etkileyen ve erken teşhis tedavi edilmediği takdirde ölüme neden olan nöropsikiyatrik bir hastalıktır. Erken tanı için yaygın olarak kullanılan yöntemlerden biri elektroensefalografidir (EEG). Sinyal işleme makine öğrenme yöntemlerinin EEG sinyallerine uygulanması, SZ hastalığını belirlemek isteyen uzmanlara araştırmacılara destek olabilir. Bu çalışmada, hastası sağlıklı kontrol grubuna işitsel uyaranların gönderilmesi sonucunda kaydedilen...
Communication is the proper transfer of feelings and thoughts to others. The most used communication among people verbal communication, which based on hearing speech. However, it observed that individuals with disabilities due or speech loss either do not use this method can limitedly. These communicate each other through methods such as sign language, alphabet created using hand finger movements. In study, a system perceive language has been developed for impairments in order more easily...
The coronavirus disease, namely Covid-19 infection, which was declared a worldwide epidemic by the World Health Organization (WHO) in 2020, first seen Wuhan, China last months of 2019 and has affected whole world. Early diagnosis this rapidly spreading is important to prevent disease. For reason, methods such as image processing, deep learning, machine learning have become detect early. In study, it been tried classify individuals who test positive negative for based on some laboratory...
Many people suffer from heart disease around the world. To problems of with understand, it is important that monitor movements and intervene immediately. One ways to examine Electrocardiography individuals. In this study, a low-cost ECG device was designed using PIC18FF4550 microcontroller. device, signal received individual displayed on LCD screen, which set as Turkish interface. At same time, thanks Bluetooth module in can be monitored simultaneously electronic devices such phones,...