Cargando…
Brain-Computer Interface Channel-Selection Strategy Based on Analysis of Event-Related Desynchronization Topography in Stroke Patients
In the last decade, technology-assisted stroke rehabilitation has been the focus of research. Electroencephalogram- (EEG-) based brain-computer interface (BCI) has a great potential for motor rehabilitation in stroke patients since the closed loop between motor intention and the actual movement esta...
Autores principales: | Li, Chong, Jia, Tianyu, Xu, Quan, Ji, Linhong, Pan, Yu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6735216/ https://www.ncbi.nlm.nih.gov/pubmed/31559004 http://dx.doi.org/10.1155/2019/3817124 |
Ejemplares similares
-
Tailoring brain–machine interface rehabilitation training based on neural reorganization: towards personalized treatment for stroke patients
por: Jia, Tianyu, et al.
Publicado: (2022) -
The Differences Between Motor Attempt and Motor Imagery in Brain-Computer Interface Accuracy and Event-Related Desynchronization of Patients With Hemiplegia
por: Chen, Shugeng, et al.
Publicado: (2021) -
Domain knowledge-assisted multi-objective evolutionary algorithm for channel selection in brain-computer interface systems
por: Liu, Tianyu, et al.
Publicado: (2023) -
Evolutionary Multitasking-Based Multiobjective Optimization Algorithm for Channel Selection in Hybrid Brain Computer Interfacing Systems
por: Liu, Tianyu, et al.
Publicado: (2021) -
Psilocybin desynchronizes brain networks
por: Siegel, Joshua S, et al.
Publicado: (2023)