Publication:
Paralyzed patients‑oriented electroencephalogram signals processing using convolutional neural network through python

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dc.contributor.authorTOPUZ, VEDAT
dc.contributor.authorAK, AYÇA
dc.contributor.authorsTopuz V., Ak A.
dc.date.accessioned2023-01-03T07:37:25Z
dc.date.available2023-01-03T07:37:25Z
dc.date.issued2022-12-01
dc.description.abstractAim: Some of the systems that use brain–computer interfaces (BCIs) that translate brain activity patterns into commands for an interactive application make use of samples produced by motor imagery. This study focuses on processing electroencephalogram (EEG) signals using convolutional neural network (CNN). It is aimed to analyze EEG signals using Python, convert data to spectrogram, and classify them with CNN in this article. Materials and Methods: EEG data used were sampled at a sampling frequency of 128 Hz, in the range of 0.5–50 Hz. The EEG file is processed using Python programming language. Spectrogram images of the channels were obtained with the Python YASA library. Results: The success of the CNN model applied to dataset was found to be 89.58%. Conclusion: EEG signals make it possible to detect diseases using various machine learning methods. Deep learning-based CNN algorithms can also be used for this purpose.
dc.identifier.citationTopuz V., Ak A., "Paralyzed Patients‑oriented Electroencephalogram Signals Processing Using Convolutional Neural Network Through Python", The Journal of Neurobehavioral Sciences, cilt.9, sa.6, ss.90-95, 2022
dc.identifier.doihttps://www.jnbsjournal.com/temp/JNeurobehavSci9390-2632077_071840.pdf
dc.identifier.endpage95
dc.identifier.issue6
dc.identifier.startpage90
dc.identifier.urihttps://hdl.handle.net/11424/284740
dc.identifier.volume9
dc.language.isoeng
dc.relation.ispartofThe Journal of Neurobehavioral Sciences
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectMühendislik ve Teknoloji
dc.subjectEngineering and Technology
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.subjectEngineering, Computing & Technology (ENG)
dc.subjectElectroencephalogram
dc.subjectconvolutional neural network
dc.subjectspectrogram images
dc.titleParalyzed patients‑oriented electroencephalogram signals processing using convolutional neural network through python
dc.typearticle
dspace.entity.typePublication
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relation.isAuthorOfPublication.latestForDiscoveryc4c753c0-313d-4b6b-bdd7-b643fcee5921

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