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Doç. Dr. Zeki ORALHANElektrik-Elektronik Mühendisliği
Erişime Açık

2 Stages-region-based p300 speller in brain-computer ınterface

Zeki ORALHAN

Brain–computer interface (BCI) applications present communication model without using peripheral nerves and neuromuscular systems. The P300 waves are used in BCI applications. Signal classification accuracy is a significant parameter for P300 BCI application. In this study, our goal is to investigate P300 speller structure for higher classification accuracy. There are a lot studies about P300 speller variations of stimulus model. This models mostly includes about row–column-based visual or audio stimuli model P300 spellers. But there is not enough study about region-based P300 spellers. This s ...Daha fazlası

Makale/Derleme 2019 IETE Journal of Research 5 Görüntülenme
Erişime Açık

A new paradigm for region-based p300 speller in brain computer ınterface

Zeki ORALHAN

Electroencephalography-based brain computer interface systems could provide alternative communication methods for severely disabled people who cannot use their neuromuscular systems. The P300 signal is one of the event related potentials that are used for brain computer interface systems. The most important performance parameter of a P300 based brain computer interface system is information transfer rate that is calculated by using classification accuracy and P300 signal detection time. Moreover, P300 speller has a very critical role for classification accuracy and information transfer rate in ...Daha fazlası

Makale/Derleme 2019 IEEE Access 8 Görüntülenme
Erişime Açık

Advanced SSVEP stimulator for brain-computer ınterface and signal classification with using convolutional neural network

Zeki ORALHAN

Steady-state visual evoked potential, type of electroencephalography (EEG) signal, that is used for brain–computer interface systems are considered in this Letter. Steady-state visual evoked potential stimulator is needed for realising the signal on the scalp. Besides, information transfer rate is the most significant parameter to evaluate overall performance of a brain–computer interface. EEG signal classification methods, task completion time, and signal stimulator structure affect information transfer rate values. In this Letter, the authors aimed to reach a high information transfer rate b ...Daha fazlası

Makale/Derleme 2019 Electronics Letter 4 Görüntülenme
Erişime Açık

3D Input convolutional neural networks for p300 signal detection

Zeki ORALHAN

P300 signal is an endogenous event related potential component. It is mostly elicited from the frontal to parietal brain lobes. Electroencephalography is used for acquiring P300 signal from scalp. P300 signal is used for brain-computer interface systems. P300 based brain-computer interface systems are preferable since they have high overall performance. The most significant overall performance indicator is information transfer rate for P300 based brain-computer interface systems. P300 signal detection accuracy and P300 detection time are using for information transfer rate calculation. Hence, ...Daha fazlası

Makale/Derleme 2020 IEEE ACCESS 10 Görüntülenme
Erişime Açık

Modeling of compulsive behavior types of obsessive-compulsive disorder patients by using the data mining method

Şaban KARAYAĞIZ | Burcu ORALHAN | Zeki ORALHAN

Data mining is a method that is used to find data that are precise, previously uncertain, and logical values from a comprehensive set of information. Data mining is used as a tool for determining the accuracy of classifications of data obtained in the field of bioinformatics by using different algorithm approaches. In this study, the data mining method was used to classify the accuracy of different algorithms and predict the types of compulsive behavior of patients with obsessive compulsive disorder. Data collected from a total of 164 people, 70 males and 94 females, were analyzed. The age ran ...Daha fazlası

Makale/Derleme 2022 Computational and Mathematical Methods in Medicine , pp. 1 - 9 4 Görüntülenme
Erişime Açık

3D Input convolutional neural network for SSVEP classification in design of brain computer interface for patient user

Zeki ORALHAN | Burcu ORALHAN

This research was aimed at presenting performance of 3-dimensional input convolutional neural networks for steady-state visual evoked potential classification in a wireless EEG-based brain-computer interface system. Overall performance of a brain-computer interface system depends on information transfer rate. Parameters such as signal classification accuracy rate, signal stimulator structure, and user task completion time affect information transfer rate. In this study, we used 3 types of signal classification methods that are 1-dimensional, 2-dimensional, and 3-dimensional input convolutional ...Daha fazlası

Makale/Derleme 2022 Computational and Mathematical Methods in Medicine , pp. 1 - 6 4 Görüntülenme
Erişime Açık

Akaryakıt istasyonları yakıt satış otomasyonu ve veri madenciliği

Zeki ORALHAN | Burcu ORALHAN

Bilimsel Araştırma Etkinlikleri

Bilimsel Araştırma Etkinlikleri 2022 yok 8 Görüntülenme
6698 sayılı Kişisel Verilerin Korunması Kanunu kapsamında yükümlülüklerimiz ve çerez politikamız hakkında bilgi sahibi olmak için alttaki bağlantıyı kullanabilirsiniz.
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