High performance clean versus artifact dry electrode EEG data classification using Convolutional Neural Network transfer learning

OBJECTIVE: Convolutional Neural Networks (CNNs) are promising for artifact detection in electroencephalography (EEG) data, but require large amounts of data. Despite increasing use of dry electrodes for EEG data acquisition, dry electrode EEG datasets are sparse. We aim to develop an algorithm for c...

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Detalles Bibliográficos
Autores principales: van Stigt, M.N., Groenendijk, E.A., Marquering, H.A., Coutinho, J.M., Potters, W.V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196906/
https://www.ncbi.nlm.nih.gov/pubmed/37215683
http://dx.doi.org/10.1016/j.cnp.2023.04.002

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196906/
https://www.ncbi.nlm.nih.gov/pubmed/37215683
http://dx.doi.org/10.1016/j.cnp.2023.04.002

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