Cargando…
Discriminating three motor imagery states of the same joint for brain-computer interface
The classification of electroencephalography (EEG) induced by the same joint is one of the major challenges for brain-computer interface (BCI) systems. In this paper, we propose a new framework, which includes two parts, feature extraction and classification. Based on local mean decomposition (LMD),...
Autores principales: | Guan, Shan, Li, Jixian, Wang, Fuwang, Yuan, Zhen, Kang, Xiaogang, Lu, Bin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8395581/ https://www.ncbi.nlm.nih.gov/pubmed/34513337 http://dx.doi.org/10.7717/peerj.12027 |
Ejemplares similares
-
Multiclass Motor Imagery Recognition of Single Joint in Upper Limb Based on NSGA- II OVO TWSVM
por: Guan, Shan, et al.
Publicado: (2018) -
Semi-supervised generative and discriminative adversarial learning for motor imagery-based brain–computer interface
por: Ko, Wonjun, et al.
Publicado: (2022) -
Vividness of Visual Imagery and Personality Impact Motor-Imagery Brain Computer Interfaces
por: Leeuwis, Nikki, et al.
Publicado: (2021) -
EEG datasets for motor imagery brain–computer interface
por: Cho, Hohyun, et al.
Publicado: (2017) -
Closed-loop motor imagery EEG simulation for brain-computer interfaces
por: Shin, Hyonyoung, et al.
Publicado: (2022)