Dynamic stopping improves the speed and accuracy of a p300 speller

Authors:
Hannes Verschore;Pieter-Jan Kindermans;David Verstraeten;Benjamin Schrauwen
Affiliations:
ELIS, Ghent University, Ghent, Belgium;ELIS, Ghent University, Ghent, Belgium;ELIS, Ghent University, Ghent, Belgium;ELIS, Ghent University, Ghent, Belgium
Venue:
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Year:
2012

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Abstract

Brain Computer Interface spellers based on the P300 paradigm traditionally use a fixed number of epochs (stimulus presentations) to predict a letter. In this contribution, we introduce a dynamical adjustment of the number of epochs based on a threshold on the confidence of a probabilistic classifier. This allows the average required number of epochs to be lowered drastically. As such, using a conceptually simple modification with no impact on computational requirements, we obtain a P300 speller which is not only faster but also more accurate, which in turn increases the usability of the system substantially.