Brain-computer Interface Signal Processing
Brain–Computer Interface Signal Processing is a specialized methodology within neurophysiological signal analysis that transforms electrophysiological brain activity, particularly electroencephalogram signals, into machine-readable commands through feature extraction, classification, and real-time decoding mechanisms to establish direct communication pathways between the brain and external devices.
2.2K
Publications
148.7K
Citations
5.3K
Authors
1.6K
Institutions
Publications per year
2017–2026
802
2.2K
Optimizing Spatial filters for Robust EEG Single-Trial Analysis
Benjamin Blankertz, Ryota Tomioka, Steven Lemm et al. · IEEE Signal Processing Magazine · 2008 · 2.1K citations
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5.3K
42
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New York State Department of Health, United States
40 publications · 15.8K citations
36
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33
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30
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New York State Department of Health, United States
31 publications · 11.3K citations
30
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1.6K
Graz University of Technology
Graz, Austria
56 h-index
254 publications
42.4K citations
Wadsworth Center
Albany, United States
45 h-index
132 publications
43.8K citations
New York State Department of Health
Albany, United States
43 h-index
122 publications
44.9K citations

University of Tübingen
Tübingen, Germany
40 h-index
198 publications
42.8K citations
Tsinghua University
Beijing, China
37 h-index
213 publications
27K citations
University of California San Diego
San Diego, United States
36 h-index
114 publications
14.2K citations
Technische Universität Berlin
Berlin, Germany
35 h-index
146 publications
25.3K citations
University of Würzburg
Würzburg, Germany
30 h-index
73 publications
8.9K citations
1–8 of 1.6K
132 publications · 16K citations
66
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126 publications · 11.6K citations
53
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63 publications · 14.5K citations
46
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41 publications · 3.7K citations
34
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47 publications · 4.6K citations
28
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