A Parallel Multiscale Filter Bank Convolutional Neural Networks for Motor Imagery EEG Classification

OBJECTIVE: Electroencephalogram (EEG) based brain–computer interfaces (BCI) in motor imagery (MI) have developed rapidly in recent years. A reliable feature extraction method is essential because of a low signal-to-noise ratio (SNR) and time-dependent covariates of EEG signals. Because of efficient...

Descripción completa

Detalles Bibliográficos
Autores principales: Wu, Hao, Niu, Yi, Li, Fu, Li, Yuchen, Fu, Boxun, Shi, Guangming, Dong, Minghao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6901997/
https://www.ncbi.nlm.nih.gov/pubmed/31849587
http://dx.doi.org/10.3389/fnins.2019.01275

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6901997/
https://www.ncbi.nlm.nih.gov/pubmed/31849587
http://dx.doi.org/10.3389/fnins.2019.01275

Ejemplares similares