Original paper
Machine-Learning-Based Coadaptive Calibration for Brain-Computer Interfaces
Abstract
Brain-computer interfaces (BCIs) allow users to control a computer application by brain activity as acquired (e.g., by EEG). In our classic machine learning approach to BCIs, the participants undertake a calibration measurement without feedback to acquire data to train the BCI system. After the training, the user can control a BCI and improve the operation through some type of feedback. However, not all BCI users are able to perform sufficiently...
Paper Details
Title
Machine-Learning-Based Coadaptive Calibration for Brain-Computer Interfaces
Published Date
Mar 1, 2011
Journal
Volume
23
Issue
3
Pages
791 - 816
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