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Determining Optimal Feature-Combination for LDA Classification of Functional Near-Infrared Spectroscopy Signals in Brain-Computer Interface Application
In this study, we determine the optimal feature-combination for classification of functional near-infrared spectroscopy (fNIRS) signals with the best accuracies for development of a two-class brain-computer interface (BCI). Using a multi-channel continuous-wave imaging system, mental arithmetic sign...
Gespeichert in:
| Veröffentlicht in: | Front Hum Neurosci |
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| Hauptverfasser: | , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Frontiers Media S.A.
2016
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4879140/ https://ncbi.nlm.nih.gov/pubmed/27252637 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnhum.2016.00237 |
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