Brain-computer Interface Training Protocols
Brain-Computer Interface Training Protocols is a systematic framework comprising standardized procedures and adaptive algorithms designed to guide the calibration, user learning, and performance optimization processes in brain-computer interface systems, distinguishing it from general neurofeedback or brain stimulation protocols by its specific integration of real-time neural signal decoding and closed-loop feedback tailored to assist users in effectively modulating their neural activity for direct device control.
70
Publications
3.8K
Citations
306
Authors
149
Institutions
Publications per year
2017–2026
32
Parents
70
1–5 of 70
306
5
h-index
Laboratoire Bordelais de Recherche en Informatique, France
5 publications · 588 citations
5
h-index
4
h-index
4
h-index
Laboratoire Bordelais de Recherche en Informatique, France
3 publications · 250 citations
3
h-index
1–5 of 306
149
Graz University of Technology
Graz, Austria
7 h-index
19 publications
1.7K citations
Laboratoire Bordelais de Recherche en Informatique
Talence, France
4 h-index
12 publications
1.2K citations

University of Tübingen
Tübingen, Germany
3 h-index
7 publications
262 citations
Centre Inria de l'université de Bordeaux
Talence, France
3 h-index
13 publications
1.3K citations

Shanghai Jiao Tong University
Shanghai, China
3 h-index
5 publications
185 citations
University of Ulster
Coleraine, United Kingdom
3 h-index
11 publications
1.3K citations
Université de Bordeaux
Bordeaux, France
3 h-index
12 publications
830 citations
University of Würzburg
Würzburg, Germany
3 h-index
6 publications
432 citations
1–8 of 149
5 publications · 477 citations
5
h-index
4 publications · 354 citations
4
h-index
3 publications · 278 citations
3
h-index
3 publications · 229 citations
3
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2 publications · 88 citations
2
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1–5