Learning Optimal Time-Frequency-Spatial Features by the CiSSA-CSP Method for Motor Imagery EEG Classification

The common spatial pattern (CSP) is a popular method in feature extraction for motor imagery (MI) electroencephalogram (EEG) classification in brain–computer interface (BCI) systems. However, combining temporal and spectral information in the CSP-based spatial features is still a challenging issue,...

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Detalles Bibliográficos
Autores principales: Hu, Hai, Pu, Zihang, Li, Haohan, Liu, Zhexian, Wang, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9658317/
https://www.ncbi.nlm.nih.gov/pubmed/36366225
http://dx.doi.org/10.3390/s22218526

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9658317/
https://www.ncbi.nlm.nih.gov/pubmed/36366225
http://dx.doi.org/10.3390/s22218526

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