Publication Type

Journal Article

Publication Date

3-2006

Abstract

We report the implementation of a text input application (speller) based on the P300 event related potential. We obtain high accuracies by using an SVM classifier and a novel feature. These techniques enable us to maintain fast performance without sacrificing the accuracy, thus making the speller usable in an online mode. In order to further improve the usability, we perform various studies on the data with a view to minimizing the training time required. We present data collected from nine healthy subjects, along with the high accuracies (of the order of 95% or more) measured online. We show that the training time can be further reduced by a factor of two from its current value of about 20 min. High accuracy, fast learning, and online performance make this P300 speller a potential communication tool for severely disabled individuals, who have lost all other means of communication and are otherwise cut off from the world, provided their disability does not interfere with the performance of the speller.

Keywords

P300, brain-computer interface, event related potential, speller, support vector machine (SVM)

Discipline

Computer Sciences | Graphics and Human Computer Interfaces

Research Areas

Data Management and Analytics

Publication

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Volume

14

Issue

1

First Page

24

Last Page

29

ISSN

1534-4320

Identifier

10.1109/TNSRE.2005.862695

Publisher

IEEE

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1109/TNSRE.2005.862695

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