Multi-scale convolutional transformer network for motor imagery brain-computer interface

Multi-scale convolutional transformer network for motor imagery brain-computer interface

Abstract Brain-computer interface (BCI) systems allow users to communicate with external devices by translating neural signals into real-time commands. Convolutional neural networks (CNNs) have been effectively utilized for decoding motor imagery electroencephalography (MI-EEG) signals in BCIs. Howe...

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Bibliographic Details
Main Authors: Wei Zhao, Baocan Zhang, Haifeng Zhou, Dezhi Wei, Chenxi Huang, Quan Lan
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Brain-computer interface (BCI)
Convolutional neural networks (CNNs)
Electroencephalography (EEG)
Motor imagery (MI)
Transformer
Online Access:https://doi.org/10.1038/s41598-025-96611-5
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