Reliability-based automatic repeat request with error potential-based error correction for improving P300 speller performance

Authors:
Hiromu Takahashi;Tomohiro Yoshikawa;Takeshi Furuhashi
Affiliations:
Nagoya University, Chikusa-ku, Nagoya, Japan;Nagoya University, Chikusa-ku, Nagoya, Japan;Nagoya University, Chikusa-ku, Nagoya, Japan
Venue:
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
Year:
2010

Citing 2
Cited 0

Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)
Online detection of p300 and error potentials in a BCI speller

Computational Intelligence and Neuroscience - Special issue on processing of brain signals by using hemodynamic and neuroelectromagnetic modalities

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.