A New Paradigm for Region-Based P300 Speller in Brain Computer Interface

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dc.authoridORALHAN, Zeki/0000-0003-2841-6115
dc.contributor.authorOralhan, Zeki
dc.date.accessioned2025-02-24T17:18:52Z
dc.date.available2025-02-24T17:18:52Z
dc.date.issued2019
dc.departmentFakülteler, Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Bölümü
dc.description.abstractElectroencephalography-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 a P300 based brain computer interface. Although most of studies are about row column based P300 speller in literature, region based P300 speller proved that has higher classification accuracy than row column based one. There are very few studies about region based P300 speller. This study aims to investigate methods for obtaining higher classification accuracy and information transfer rate with using region based P300 speller that constituted audio and visual stimulus. This is the first research that using audio and visual stimulus for a region based P300 speller in literature. Previous studies about region based P300 spellers focused on spellers with only visual stimulus types. Our new paradigm presents region based P300 spellers with only audio, only visual, and audio-visual stimuli. Audio-visual P300 speller structure is the newest model for region based spellers. The subject focused on the desired character stimulus. We used the stepwise linear discriminant analysis method for classification that either included the desired P300 signal or not. According to stepwise linear discriminant analysis, the mean classification accuracy value of the experiment was 90.31% with the audio-visual region based P300 speller. With this new paradigm, classification accuracy in the audio-visual P300 speller was improved 15.69% and 66,99% according to the visual only and audio only P300 speller that we used in the experiments, respectively.
dc.identifier.doi10.1109/ACCESS.2019.2933049
dc.identifier.endpage106626
dc.identifier.issn2169-3536
dc.identifier.scopus2-s2.0-85071176779
dc.identifier.scopusqualityQ1
dc.identifier.startpage106617
dc.identifier.urihttps://doi.org/10.1109/ACCESS.2019.2933049
dc.identifier.urihttps://hdl.handle.net/20.500.14440/872
dc.identifier.volume7
dc.identifier.wosWOS:000481972100103
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorOralhan, Zeki
dc.language.isoen
dc.publisherIeee-Inst Electrical Electronics Engineers Inc
dc.relation.ispartofIeee Access
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20250201
dc.subjectBrain computer interface
dc.subjectP300
dc.subjectHuman machine systems
dc.subjectP300 Speller
dc.titleA New Paradigm for Region-Based P300 Speller in Brain Computer Interface
dc.typeArticle

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