"most of the models focus on the recognition performance achieved for a single subject and are challenging to transfer due to individual differences and low signal-to-noise-ratio of EEG signals. To date, few studies have paid attention to the balance between generalizability and personalization across subjects. To this end, we propose a co-teaching graph learning method... Experimental results also demonstrate that it is easy to derive a model that can represent generic knowledge of multiple motor imagery subjects and can be fine-tuned efficiently for new subjects."
Yifan Zhang et al., "Graph Learning with Co-Teaching for EEG-Based Motor Imagery Recognition," in IEEE Transactions on Cognitive and Developmental Systems https://ieeexplore.ieee.org/abstract/document/9773344
Yifan Zhang et al., "Graph Learning with Co-Teaching for EEG-Based Motor Imagery Recognition," in IEEE Transactions on Cognitive and Developmental Systems https://ieeexplore.ieee.org/abstract/document/9773344