Cargando…
Intelligent Classification Technique of Hand Motor Imagery Using EEG Beta Rebound Follow-Up Pattern
To apply EEG-based brain-machine interfaces during rehabilitation, separating various tasks during motor imagery (MI) and assimilating MI into motor execution (ME) are needed. Previous studies were focusing on classifying different MI tasks based on complex algorithms. In this paper, we implement in...
Autores principales: | Wang, Jiachen, Chen, Yun-Hsuan, Yang, Jie, Sawan, Mohamad |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9221354/ https://www.ncbi.nlm.nih.gov/pubmed/35735532 http://dx.doi.org/10.3390/bios12060384 |
Ejemplares similares
-
Exploring the Role of Visual Guidance in Motor Imagery-Based Brain-Computer Interface: An EEG Microstate-Specific Functional Connectivity Study
por: Wang, Tianjun, et al.
Publicado: (2023) -
Hand Motor Imagery Classification Using Effective Connectivity and Hierarchical Machine Learning in EEG Signals
por: Maghsoudi, Arash, et al.
Publicado: (2022) -
Motor Imagery EEG Classification Using Capsule Networks†
por: Ha, Kwon-Woo, et al.
Publicado: (2019) -
EEG oscillatory patterns and classification of sequential compound limb motor imagery
por: Yi, Weibo, et al.
Publicado: (2016) -
Three-Class EEG-Based Motor Imagery Classification Using Phase-Space Reconstruction Technique
por: Djemal, Ridha, et al.
Publicado: (2016)