MCL-SWT: Mirror Contrastive Learning with Sliding Window Transformer for Subject-Independent EEG Recognition

MCL-SWT: Mirror Contrastive Learning with Sliding Window Transformer for Subject-Independent EEG Recognition

<b>Background</b>: In brain–computer interfaces (BCIs), transformer-based models have found extensive application in motor imagery (MI)-based EEG signal recognition. However, for subject-independent EEG recognition, these models face challenges: low sensitivity to spatial dynamics of neu...

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Bibliographic Details
Main Authors: Qi Mao, Hongke Zhu, Wenyao Yan, Yu Zhao, Xinhong Hei, Jing Luo
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Brain Sciences
Subjects:
BCI
EEG
motor imagery
contrastive learning
sliding window transformer
Online Access:https://www.mdpi.com/2076-3425/15/5/460
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