Electroencephalogram-Based Motor Imagery Classification Using Deep Residual Convolutional Networks

The classification of electroencephalogram (EEG) signals is of significant importance in brain-computer interface (BCI) systems. Aiming to achieve intelligent classification of motor imagery EEG types with high accuracy, a classification methodology using the wavelet packet decomposition (WPD) and t...

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Detalles Bibliográficos
Autores principales: Huang, Jing-Shan, Liu, Wan-Shan, Yao, Bin, Wang, Zhan-Xiang, Chen, Si-Fang, Sun, Wei-Fang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8635693/
https://www.ncbi.nlm.nih.gov/pubmed/34867174
http://dx.doi.org/10.3389/fnins.2021.774857

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8635693/
https://www.ncbi.nlm.nih.gov/pubmed/34867174
http://dx.doi.org/10.3389/fnins.2021.774857

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