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A Hierarchical Stimulus Presentation Paradigm for a P300-Based Hangul Speller

Authors
Lee, Tae-HoonKam, Tae-EuiKim, Sung-Phil
Issue Date
2011
Publisher
WILEY
Keywords
brain-computer interface; electroencephalography; P300; Hangul speller; hierarchical stimulus presentation paradigm
Citation
INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, v.21, no.2, pp.131 - 138
Indexed
SCIE
SCOPUS
Journal Title
INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY
Volume
21
Number
2
Start Page
131
End Page
138
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/114899
DOI
10.1002/ima.20282
ISSN
0899-9457
Abstract
We propose a hierarchical stimulus presentation paradigm for a P300-based Hangul (Korean script) input system. A P300-based input system (or speller) is one of the most promising noninvasive brain-computer interface (BCI) applications based on its direct applicability in many computer programs. Although the previous row/column stimulus presentation paradigm has been well-suited to the English input, it may not be optimal for a Hangul input because Hangul has a distinct hierarchical structure. To overcome the limitation of the previous paradigms, we developed a new P300-based Hangul input system by taking the unique hierarchical structure of Hangul into account for creating a hierarchical stimulus presentation paradigm. By using the hierarchical structure, we can effectively reduce the window size of the interface without loss of classification accuracy. A performance comparison shows that the hierarchical paradigm exhibits higher classification accuracy than the row/column paradigm even with a smaller window size. Thus, the proposed hierarchical paradigm is more efficient to spell Hangul and will be more useful for BCI-based Hangul input for a text messenger, e-mail program, word processor and other similar applications. (C) 2011 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 21, 131-138, 2011; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/ima.20282
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Graduate School > Department of Artificial Intelligence > 1. Journal Articles
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