Cargando…
Recognition of EEG Signal Motor Imagery Intention Based on Deep Multi-View Feature Learning
Recognition of motor imagery intention is one of the hot current research focuses of brain-computer interface (BCI) studies. It can help patients with physical dyskinesia to convey their movement intentions. In recent years, breakthroughs have been made in the research on recognition of motor imager...
Autores principales: | Xu, Jiacan, Zheng, Hao, Wang, Jianhui, Li, Donglin, Fang, Xiaoke |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349253/ https://www.ncbi.nlm.nih.gov/pubmed/32575798 http://dx.doi.org/10.3390/s20123496 |
Ejemplares similares
-
Deep temporal networks for EEG-based motor imagery recognition
por: Sharma, Neha, et al.
Publicado: (2023) -
Motor Imagery EEG Signal Recognition Using Deep Convolution Neural Network
por: Xiao, Xiongliang, et al.
Publicado: (2021) -
Spatial-Frequency Feature Learning and Classification of Motor Imagery EEG Based on Deep Convolution Neural Network
por: Miao, Minmin, et al.
Publicado: (2020) -
On the Deep Learning Models for EEG-Based Brain-Computer Interface Using Motor Imagery
por: Zhu, Hao, et al.
Publicado: (2022) -
Dynamic pruning group equivariant network for motor imagery EEG recognition
por: Tang, Xianlun, et al.
Publicado: (2023)