Classification of motor imagery signals by convolutional neural network for BCI applications

dc.contributor.authorBalim, Mustafa Alper
dc.contributor.authorAcir, Nurettin
dc.date.accessioned2026-02-12T21:02:48Z
dc.date.available2026-02-12T21:02:48Z
dc.date.issued2019
dc.departmentBursa Teknik Üniversitesi
dc.description27th Signal Processing and Communications Applications Conference, SIU 2019 -- 2019-04-24 through 2019-04-26 -- Sivas -- 151073
dc.description.abstractElectroencephalography (EEG) signals have been using for clinical purposes for many years. However, studies on the use of EEG signals in brain computer interface (BBA) applications are increasing. It is possible to control machines using only mental activities, especially for patients with limited mobility. Motor imagery signals (MIS) which are formed as a result of the imagination of moving a limb are one of the most common signal used for this purpose. In this study, it is aimed to classify MIS signals with Convolutional Neural Network by using BCI-IV 2b dataset. As a result, higher (%75,7) performance was obtained with lower number of parameters compared to similar previous studies. © 2019 IEEE.
dc.identifier.doi10.1109/SIU.2019.8806474
dc.identifier.isbn9781728119045
dc.identifier.scopus2-s2.0-85071966257
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/SIU.2019.8806474
dc.identifier.urihttps://hdl.handle.net/20.500.12885/6547
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof27th Signal Processing and Communications Applications Conference, SIU 2019
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.snmzKA_Scopus_20260212
dc.subjectBrain computer interface
dc.subjectDeep learning
dc.subjectElectroencephalography
dc.subjectMotor imagery
dc.titleClassification of motor imagery signals by convolutional neural network for BCI applications
dc.title.alternativeBBA Uygulamalari için Hayali Motor Işaretlerinin Evrişimsel Sinir Ağlari ile Siniflandirilmasi
dc.typeConference Object

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