AMEEGNet: attention-based multiscale EEGNet for effective motor imagery EEG decoding

AMEEGNet: attention-based multiscale EEGNet for effective motor imagery EEG decoding

Recently, electroencephalogram (EEG) based on motor imagery (MI) have gained significant traction in brain-computer interface (BCI) technology, particularly for the rehabilitation of paralyzed patients. But the low signal-to-noise ratio of MI EEG makes it difficult to decode effectively and hinders...

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Bibliographic Details
Main Authors: Xuejian Wu, Yaqi Chu, Qing Li, Yang Luo, Yiwen Zhao, Xingang Zhao
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Neurorobotics
Subjects:
motor imagery (MI) EEG
brain-computer interface
signal decoding
multi-scale decoding
fusion transmission
efficient channel attention (ECA) mechanism
Online Access:https://www.frontiersin.org/articles/10.3389/fnbot.2025.1540033/full
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