Functional Connectivity and Feature Fusion Enhance Multiclass Motor-Imagery Brain–Computer Interface Performance

(1) Background: in the field of motor-imagery brain–computer interfaces (MI-BCIs), obtaining discriminative features among multiple MI tasks poses a significant challenge. Typically, features are extracted from single electroencephalography (EEG) channels, neglecting their interconnections, which le...

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Detalles Bibliográficos
Autores principales: Siviero, Ilaria, Menegaz, Gloria, Storti, Silvia Francesca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490741/
https://www.ncbi.nlm.nih.gov/pubmed/37687976
http://dx.doi.org/10.3390/s23177520

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490741/
https://www.ncbi.nlm.nih.gov/pubmed/37687976
http://dx.doi.org/10.3390/s23177520

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