Transfer Learning for SSVEP Electroencephalography Based Brain–Computer Interfaces Using Learn++.NSE and Mutual Information

Transfer Learning for SSVEP Electroencephalography Based Brain–Computer Interfaces Using Learn++.NSE and Mutual Information

Brain–Computer Interfaces (BCI) using Steady-State Visual Evoked Potentials (SSVEP) are sometimes used by injured patients seeking to use a computer. Canonical Correlation Analysis (CCA) is seen as state-of-the-art for SSVEP BCI systems. However, this assumes that the user has full control over thei...

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Bibliographic Details
Main Authors: Matthew Sybeldon, Lukas Schmit, Murat Akcakaya
Format: Article
Language:English
Published: MDPI AG 2017-01-01
Series:Entropy
Subjects:
BCI
electroencephalography
SSVEP
transfer learning
mutual information
Learn++.NSE
canonical correlation analysis
Online Access:http://www.mdpi.com/1099-4300/19/1/41

Internet

http://www.mdpi.com/1099-4300/19/1/41

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