Bidirectional feature pyramid attention-based temporal convolutional network model for motor imagery electroencephalogram classification

Bidirectional feature pyramid attention-based temporal convolutional network model for motor imagery electroencephalogram classification

IntroductionAs an interactive method gaining popularity, brain-computer interfaces (BCIs) aim to facilitate communication between the brain and external devices. Among the various research topics in BCIs, the classification of motor imagery using electroencephalography (EEG) signals has the potentia...

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Bibliographic Details
Main Authors: Xinghe Xie, Liyan Chen, Shujia Qin, Fusheng Zha, Xinggang Fan
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-01-01
Series:Frontiers in Neurorobotics
Subjects:
deep learning
temporal convolutional networks
multihead attention
electroencephalogram
motion imagery
Online Access:https://www.frontiersin.org/articles/10.3389/fnbot.2024.1343249/full

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https://www.frontiersin.org/articles/10.3389/fnbot.2024.1343249/full

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