AI RESEARCH
BCI-sift: An automated feature selection toolbox for Brain Computer Interface applications
arXiv CS.LG
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ArXi:2605.19646v1 Announce Type: cross Advancements in clinical Brain-Computer Interfaces (BCIs) depend on precise and reliable signal interpretation. However, the high-dimensional and noisy nature of data captured from both implanted and non-implanted BCIs poses significant challenges, motivating the use of feature selection algorithms. We