Comparison of the performances of selected EEG electrodes with optimization algorithms in P300 based speller systems

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dc.authorid0000-0003-1728-6087
dc.authorid0000-0003-1840-9958
dc.authorscopusid57203004568
dc.authorscopusid8945093900
dc.contributor.authorArıcan, Murat
dc.contributor.authorPolat, Kemal
dc.date.accessioned2024-09-25T19:42:52Z
dc.date.available2024-09-25T19:42:52Z
dc.date.issued2019
dc.departmentBAİBÜ, Lisansüstü Eğitim Enstitüsü, Fen Bilimleri, Elektrik Elektronik Mühendisliği Ana Bilim Dalıen_US
dc.description2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019 -- 24 April 2019 through 26 April 2019 -- Istanbul -- 148870en_US
dc.description.abstractNowadays, the evoked potentials obtained from EEG signals are frequently used in Brain Computer Interfaces (BCI) in order to ensure that individuals with complete paralysis are communicated with the environment. However, EEG signals have a multi-channel structure due to the nature, and this situation increases the data size. Therefore, the working costs of BCIs are increasing. At this stage, reduce the number of electrodes is a solution to reduce the process speed and load in BCI systems. Different techniques are used for this purpose. Some of these are the optimization methods produced by the movement of living beings in nature. In this study, the effects of reduced channels by using Bee Algorithm (BA), Particle Swarm Algorithm (PSO), Differential Evolution (DE), Genetic Algorithm (GA) used in P300 hyphenation systems to reduce the number of electrodes were investigated. As a result of the study, between the accuracy rates obtained with 64 channels and the accuracy rates obtained with channel selecting, (the LS-SVM classifier for User B by B-BA) is seen an about 20% increase. Optimization algorithms are a suitable method to reduce the cost of system operation. © 2019 IEEE.en_US
dc.identifier.doi10.1109/EBBT.2019.8741865
dc.identifier.isbn978-172811013-4
dc.identifier.scopus2-s2.0-85068570994en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/EBBT.2019.8741865
dc.identifier.urihttps://hdl.handle.net/20.500.12491/12312
dc.indekslendigikaynakScopusen_US
dc.institutionauthorPolat, Kemal
dc.institutionauthorArıcan, Murat
dc.institutionauthorid0000-0003-1728-6087
dc.institutionauthorid0000-0003-1840-9958
dc.language.isotren_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2019 Scientific Meeting on Electrical-Electronics and Biomedical Engineering and Computer Science, EBBT 2019en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - İdari Personel ve Öğrencien_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzYK_20240925en_US
dc.subjectBrain Computer Interfaceen_US
dc.subjectElectrode Selectionen_US
dc.subjectEvent Related Potentialen_US
dc.subjectLS-SVMen_US
dc.subjectP300en_US
dc.titleComparison of the performances of selected EEG electrodes with optimization algorithms in P300 based speller systemsen_US
dc.title.alternativeP300 tabanlı heceleme sistemelerinde en iyileme algoritmaları ile seçilen EEG elektrotlarının başarımlarının karşılaştırılmasıen_US
dc.typeConference Objecten_US

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