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Personalized Offline and Pseudo-Online BCI Models to Detect Pedaling Intent
The aim of this work was to design a personalized BCI model to detect pedaling intention through EEG signals. The approach sought to select the best among many possible BCI models for each subject. The choice was between different processing windows, feature extraction algorithms and electrode confi...
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| Pubblicato in: | Front Neuroinform |
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| Autori principali: | , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Frontiers Media S.A.
2017
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5504298/ https://ncbi.nlm.nih.gov/pubmed/28744212 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fninf.2017.00045 |
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