Cargando…
Hand Motor Imagery Classification Using Effective Connectivity and Hierarchical Machine Learning in EEG Signals
BACKGROUND: Motor Imagery (MI) Brain Computer Interface (BCI) directly links central nervous system to a computer or a device. Most MI-BCI structures rely on features of a single channel of Electroencephalogram (EEG). However, to provide more valuable features, the relationships among EEG channels i...
Autores principales: | Maghsoudi, Arash, Shalbaf, Ahmad |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Shiraz University of Medical Sciences
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8995751/ https://www.ncbi.nlm.nih.gov/pubmed/35433527 http://dx.doi.org/10.31661/jbpe.v0i0.1264 |
Ejemplares similares
-
Mental Arithmetic Task Recognition Using Effective Connectivity and Hierarchical Feature Selection From EEG Signals
por: Maghsoudi, Arash, et al.
Publicado: (2021) -
A Hybrid EEG-based Emotion Recognition Approach Using Wavelet Convolutional Neural Networks and Support Vector Machine
por: Bagherzadeh, Sara, et al.
Publicado: (2023) -
Sparse Representation-Based Extreme Learning Machine for Motor Imagery EEG Classification
por: She, Qingshan, et al.
Publicado: (2018) -
Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization
por: Ma, Yuliang, et al.
Publicado: (2016) -
Assessment of Anesthesia Depth Using Effective Brain Connectivity Based on Transfer Entropy on EEG Signal
por: Sanjari, Neda, et al.
Publicado: (2021)