Group-member selection for RSVP-based collaborative brain-computer interfaces
The results showed that our proposed MIMC effectively optimized the group mode, enhanced the classification performance in the two-user matching task, and could reduce the redundant information by selecting the sub-group in the RSVP-based multi-user cBCI systems.
Authors
- Ting Zhou (ORCID: https://orcid.org/0000-0002-0420-0566)
- Honglin Hu (ORCID: https://orcid.org/0000-0002-4665-5278)
- Guiying Xu (ORCID: https://orcid.org/0000-0001-8191-3933)
- Tianheng Xu (ORCID: https://orcid.org/0000-0002-7152-1378)
- Zhenyu Wang (ORCID: https://orcid.org/0000-0002-4857-7234)
- Yuan Si (ORCID: https://orcid.org/0009-0001-3645-4632)
- Zikai Wang (ORCID: https://orcid.org/0000-0002-1545-0616)
Institutions
- Shanghai University (CN)
- Chinese Academy of Sciences (CN)
- Shanghai Advanced Research Institute (CN)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- Frontiers in Neuroscience
- Published
- 2024-08-21
- DOI
- https://doi.org/10.3389/fnins.2024.1402154
- Citations
- 3
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 1.03