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A Dictionary-Driven P300 Speller With a Modified Interface

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3 Author(s)
Sercan Taha Ahi ; Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology, Yokohama, Japan ; Hiroyuki Kambara ; Yasuharu Koike

P300 spellers are mainly composed of an interface, by which alphanumerical characters are presented to users, and a classification system, which identifies the target character by using acquired EEG data. In this study, we proposed modifications both to the interface and to the classification system, in order to reduce the number of required stimulus repetitions and consequently boost the information transfer rate. We initially incorporated a custom-built dictionary into the classification system, and conducted a study on 14 healthy subjects who copy-spelled 15 four letter words. Incorporating the dictionary, the mean accuracy at five trials increased from 72.86% to 95.71%. To further increase the system performance, we first validated the hypothesis that for a conventional P300 system, most target-error pairs lie on the same row or column. Then based on the validated hypothesis, we adjusted letter positions on the well-known from A to Z interface. The same subjects spelled the same 15 words using the modified interface as well, and the mean information transfer rate at two trials reached 55.32 bits/min.

Published in:

IEEE Transactions on Neural Systems and Rehabilitation Engineering  (Volume:19 ,  Issue: 1 )