A composite improved attention convolutional network for motor imagery EEG classification

A composite improved attention convolutional network for motor imagery EEG classification

IntroductionA brain-computer interface (BCI) is an emerging technology that aims to establish a direct communication pathway between the human brain and external devices. Motor imagery electroencephalography (MI-EEG) signals are analyzed to infer users’ intentions during motor imagery. These signals...

Full description

Saved in:
Bibliographic Details
Main Authors: Wenzhe Liao, Zipeng Miao, Shuaibo Liang, Linyan Zhang, Chen Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Neuroscience
Subjects:
electroencephalography
convolution neural network
attention mechanism
temporal convolution network
motor imagery
classification
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2025.1543508/full
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.frontiersin.org/articles/10.3389/fnins.2025.1543508/full

Similar Items