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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Reliability-Based Automatic Repeat reQuest with Error Potential-Based Error Correction for Improving P300 Speller Performance
verfasst von : Hiromu Takahashi, Tomohiro Yoshikawa, Takeshi Furuhashi
Erschienen in: Neural Information Processing. Models and Applications
Verlag: Springer Berlin Heidelberg
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The P300 speller allows users to select letters just by thoughts. However, due to the low signal-to-noise ratio of the P300 response, signal averaging is often performed, which improves the spelling accuracy but degrades the spelling speed. The authors have proposed
reliability-based automatic repeat request
(RB-ARQ) to ease this problem. RB-ARQ could be enhanced when it is combined with the error correction based on the error-related potentials. This paper presents how to combine both methods and how to optimize parameters to maximize the performance of the P300 speller. The result shows that the performance was improved by 40 percent on average.