Beyin Bilgisayar Arayüzü Uygulamalari için Dinlenme, Harekete Niyet ve Hareket Ayırma

dc.contributor.author Oztürk, Nedime
dc.contributor.author Yilmaz, Bulent
dc.date.accessioned 2025-09-25T10:37:12Z
dc.date.available 2025-09-25T10:37:12Z
dc.date.issued 2018
dc.description Karakullukcu, Nedime/0000-0002-1698-3705; en_US
dc.description.abstract Brain-computer interface (BCI) is a system that provides a means to control prosthesis, wheelchair, or similar devices using brain waves without direct motor nervous system involvement. For this purpose, brain waves obtained from multiple electrodes placed on the scalp (EEG, Electroencephalogram) are used. Emotiv Epoc used to obtain EEG signals is a low-cost device and has real-time applications. The aim of this study is the detection of rest, imagination and real movement using EEG signals obtained by Emotiv Epoc headset. As a result, As a result, the data obtained from 39 trials from a female subject were classified resting, motion imagination and movement, according to 97.4% accuracy by using the statistical features of distortion, logarithm energy entropy, energy, Shannon entropy and kurtosis. In this study, it has been shown that this system can be remarkably successful for BCI applications. © 2019 Elsevier B.V., All rights reserved. en_US
dc.identifier.doi 10.1109/TIPTEKNO.2018.8597152
dc.identifier.isbn 9781538668528
dc.identifier.scopus 2-s2.0-85061758948
dc.identifier.uri https://doi.org/10.1109/TIPTEKNO.2018.8597152
dc.identifier.uri https://hdl.handle.net/20.500.12573/2935
dc.language.iso tr en_US
dc.publisher Institute of Electrical and Electronics Engineers Inc. en_US
dc.relation.ispartof -- 2018 Medical Technologies National Congress, TIPTEKNO 2018 -- Magusa -- 144203 en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Brain Computer Interface en_US
dc.subject EEG en_US
dc.subject EEG Signal Processing en_US
dc.subject First-Order Statistics Features en_US
dc.subject Motor Imagery en_US
dc.subject Biomedical Engineering en_US
dc.subject Computer Control Systems en_US
dc.subject Electroencephalography en_US
dc.subject Signal Processing en_US
dc.subject Brain-Computer Interface Applications en_US
dc.subject EEG Signal Processing en_US
dc.subject First-Order Statistics en_US
dc.subject Low-Cost Devices en_US
dc.subject Motor Imagery en_US
dc.subject Multiple Electrodes en_US
dc.subject Real-Time Application en_US
dc.subject Statistical Features en_US
dc.subject Brain Computer Interface en_US
dc.title Beyin Bilgisayar Arayüzü Uygulamalari için Dinlenme, Harekete Niyet ve Hareket Ayırma en_US
dc.title.alternative Discrimination of Rest, Motor Imagery and Movement for Brain-Computer Interface Applications en_US
dc.type Conference Object en_US
dspace.entity.type Publication
gdc.author.id Karakullukcu, Nedime/0000-0002-1698-3705
gdc.author.scopusid 57206473282
gdc.author.scopusid 57189925966
gdc.author.wosid Yılmaz, Bülent/Acr-8602-2022
gdc.author.wosid Karakullukcu, Nedime/X-2586-2019
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gdc.description.department Abdullah Gül University en_US
gdc.description.departmenttemp [Oztürk] Nedime, Elektrik Ve Bilgisayar Mühendisliǧi Bölümü, Abdullah Gül Üniversitesi, Kayseri, Turkey; [Yilmaz] Bulent, Mühendislik Fakültesi, Abdullah Gül Üniversitesi, Kayseri, Turkey en_US
gdc.description.endpage 4
gdc.description.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality N/A
gdc.description.startpage 1
gdc.description.woscitationindex Conference Proceedings Citation Index - Science
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gdc.oaire.sciencefields 03 medical and health sciences
gdc.oaire.sciencefields 0302 clinical medicine
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