02303nas a2200265   4500008004100000022001400041245007700055210006900132260000900201300001400210490000700224520143600231653001501667653003001682653002701712653003001739653001101769653002301780100002101803700002301824700002401847700001801871700002801889856012001917       2021                        eng d  a1558-021000aA Voting-Enhanced Dynamic-Window-Length Classifier for SSVEP-Based BCIs.0 aVotingEnhanced DynamicWindowLength Classifier for SSVEPBased BCI  c2021  a1766-17730 v293 a<p>We present a dynamic window-length classifier for steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) that does not require the user to choose a feature extraction method or channel set. Instead, the classifier uses multiple feature extraction methods and channel selections to infer the SSVEP and relies on majority voting to pick the most likely target. The classifier extends the window length dynamically if no target obtains the majority of votes. Compared with existing solutions, our classifier: (i) does not assume that any single feature extraction method will consistently outperform the others; (ii) adapts the channel selection to individual users or tasks; (iii) uses dynamic window lengths; (iv) is unsupervised (i.e., does not need training). Collectively, these characteristics make the classifier easy-to-use, especially for caregivers and others with limited technical expertise. We evaluated the performance of our classifier on a publicly available benchmark dataset from 35 healthy participants. We compared the information transfer rate (ITR) of this new classifier to those of the minimum energy combination (MEC), maximum synchronization index (MSI), and filter bank canonical correlation analysis (FBCCA). The new classifier increases average ITR to 123.5 bits-per-minute (bpm), 47.5, 51.2, and 19.5 bpm greater than the MEC, MSI, and FBCCA classifiers, respectively.</p>10aAlgorithms10abrain-computer interfaces10aElectroencephalography10aEvoked Potentials, Visual10aHumans10aPhotic Stimulation1 aHabibzadeh, Hadi1 aNorton, James, J S1 aVaughan, Theresa, M1 aSoyata, Tolga1 aZois, Daphney-Stavroula  uhttps://www.neurotechcenter.org/publications/2021/voting-enhanced-dynamic-window-length-classifier-ssvep-based-bcis