Feature optimization based on improved novel global harmony search algorithm for motor imagery electroencephalogram classification

BACKGROUND: Effectively decoding electroencephalogram (EEG) pattern for specific mental tasks is a crucial topic in the development of brain-computer interface (BCI). Extracting common spatial pattern (CSP) features from motor imagery EEG signals is often highly dependent on the selection of frequen...

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Detalles Bibliográficos
Autores principales: Shi, Bin, Chen, Xiaokai, Yue, Zan, Zeng, Feixiang, Yin, Shuai, Wang, Benguo, Wang, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9801329/
https://www.ncbi.nlm.nih.gov/pubmed/36589278
http://dx.doi.org/10.3389/fncom.2022.1004301

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9801329/
https://www.ncbi.nlm.nih.gov/pubmed/36589278
http://dx.doi.org/10.3389/fncom.2022.1004301

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