Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)
Brain-Computer Interfaces (BCIs) are promising technologies to restore control and communication for severely paralyzed people such as those with amyotrophic lateral sclerosis, and they can be appealied to healthy people as well. The P300 speller is one of the BCI applications, which allows users to select letters just by thoughts. However, due to the low signal-to-noise ratio of the P300, signal averaging is often performed, which improves the spelling accuracy but degrades the spelling speed. Predictive text, implemented in the most mobile phones, enables users to spell with fewer key presses; thus, it could improve the spelling speed of the P300 speller. This paper implements a predictive text to the P300 speller, and examines the usability of the interface and how the spelling speed is improved.
