A study of motor imagery EEG classification based on feature fusion and attentional mechanisms
The model demonstrates robustness to spatial resolution variations and individual differences, effectively mitigating key challenges in motor imagery EEG classification.
Authors
- Hailin Tang (ORCID: https://orcid.org/0000-0002-4090-8852)
- Zhijian Wu (ORCID: https://orcid.org/0000-0002-8449-8920)
- Shijun Li (ORCID: https://orcid.org/0000-0001-6158-4423)
- Yijia Li (ORCID: https://orcid.org/0000-0001-5300-0571)
- Lei Jiang (ORCID: https://orcid.org/0000-0003-1745-4132)
- Zhu Tingting (ORCID: https://orcid.org/0000-0002-8649-1167)
Institutions
- Wuhan University (CN)
- RPX (United States) (US)
- Guangdong Baiyun University (CN)
Publication Details
- Journal
- Frontiers in Human Neuroscience
- Published
- 2025-07-16
- DOI
- https://doi.org/10.3389/fnhum.2025.1611229
- Citations
- 3
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 4.29
Funders
- Wuhan University