Motor imagery electroencephalogram classification algorithm based on joint features in the spatial and frequency domains and instance transfer

INTRODUCTION: Motor imagery electroencephalography (MI-EEG) has significant application value in the field of rehabilitation, and is a research hotspot in the brain-computer interface (BCI) field. Due to the small training sample size of MI-EEG of a single subject and the large individual difference...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Ximiao, Dai, Xisheng, Liu, Yu, Chen, Xiangmeng, Hu, Qinghui, Hu, Rongliang, Li, Mingxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196205/
https://www.ncbi.nlm.nih.gov/pubmed/37213929
http://dx.doi.org/10.3389/fnhum.2023.1175399

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10196205/
https://www.ncbi.nlm.nih.gov/pubmed/37213929
http://dx.doi.org/10.3389/fnhum.2023.1175399

Ejemplares similares