A Chinese Text Input Brain-Computer Interface Based on the P300 Speller

James W. Minett, Hong Ying Zheng, Manson Cheuk-Man Fong, Lin Zhou, Gang Peng, William Shi Yuan Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

22 Citations (Scopus)

Abstract

A visual speller is a brain-computer interface that empowers users with limited motor functionality to input text into a computer by measuring their electroencephalographic responses to visual stimuli. Most prior research on visual spellers has focused on input of alphabetic text. Adapting a speller for other types of segmental or syllabic script is straightforward because such scripts comprise sufficiently few characters that they may all be displayed to the user simultaneously. Logographic scripts, such as Chinese hanzi, however, impose a challenge: How should the thousands of Chinese characters be displayed to the user? Here, we present a visual speller, based on Farwell and Donchin's P300 Speller, for Chinese character input. The speller uses a novel shape-based method called the First-Last, or FLAST, method to encode more than 7,000 Chinese characters. Characters are input by selecting two components, from a set of 56 distinct components, that match the shape of the target character, followed by selection of the character itself. At the input speed of one character per 107 s, 24 able-bodied participants achieved mean online accuracy of 82.8% per component selection and 63.5% per character input. At the faster input speed of one character per 77 s, mean online accuracy was 59.4% per component selection and 33.3% per character input.
Original languageEnglish
Pages (from-to)472-483
Number of pages12
JournalInternational Journal of Human-Computer Interaction
Volume28
Issue number7
DOIs
Publication statusPublished - 1 Jul 2012
Externally publishedYes

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Human-Computer Interaction
  • Computer Science Applications

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