Motor imagery EEG signal classification with a multivariate time series approach

BACKGROUND: Electroencephalogram (EEG) signals record electrical activity on the scalp. Measured signals, especially EEG motor imagery signals, are often inconsistent or distorted, which compromises their classification accuracy. Achieving a reliable classification of motor imagery EEG signals opens...

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Detalles Bibliográficos
Autores principales: Velasco, I., Sipols, A., De Blas, C. Simon, Pastor, L., Bayona, S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10035287/
https://www.ncbi.nlm.nih.gov/pubmed/36959601
http://dx.doi.org/10.1186/s12938-023-01079-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10035287/
https://www.ncbi.nlm.nih.gov/pubmed/36959601
http://dx.doi.org/10.1186/s12938-023-01079-x

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