Electroencephalogram-Based Motor Imagery Signals Classification Using a Multi-Branch Convolutional Neural Network Model with Attention Blocks

Brain signals can be captured via electroencephalogram (EEG) and be used in various brain–computer interface (BCI) applications. Classifying motor imagery (MI) using EEG signals is one of the important applications that can help a stroke patient to rehabilitate or perform certain tasks. Dealing with...

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Detalles Bibliográficos
Autores principales: Altuwaijri, Ghadir Ali, Muhammad, Ghulam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9311604/
https://www.ncbi.nlm.nih.gov/pubmed/35877374
http://dx.doi.org/10.3390/bioengineering9070323

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9311604/
https://www.ncbi.nlm.nih.gov/pubmed/35877374
http://dx.doi.org/10.3390/bioengineering9070323

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