Literature DB >> 19560965

Visual stimuli for the P300 brain-computer interface: a comparison of white/gray and green/blue flicker matrices.

Kouji Takano1, Tomoaki Komatsu, Naoki Hata, Yasoichi Nakajima, Kenji Kansaku.   

Abstract

OBJECTIVE: The white/gray flicker matrix has been used as a visual stimulus for the so-called P300 brain-computer interface (BCI), but the white/gray flash stimuli might induce discomfort. In this study, we investigated the effectiveness of green/blue flicker matrices as visual stimuli.
METHODS: Ten able-bodied, non-trained subjects performed Alphabet Spelling (Japanese Alphabet: Hiragana) using an 8 x 10 matrix with three types of intensification/rest flicker combinations (L, luminance; C, chromatic; LC, luminance and chromatic); both online and offline performances were evaluated.
RESULTS: The accuracy rate under the online LC condition was 80.6%. Offline analysis showed that the LC condition was associated with significantly higher accuracy than was the L or C condition (Tukey-Kramer, p < 0.05). No significant difference was observed between L and C conditions.
CONCLUSIONS: The LC condition, which used the green/blue flicker matrix was associated with better performances in the P300 BCI. SIGNIFICANCE: The green/blue chromatic flicker matrix can be an efficient tool for practical BCI application.

Mesh:

Year:  2009        PMID: 19560965     DOI: 10.1016/j.clinph.2009.06.002

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  41 in total

Review 1.  Brain computer interfaces, a review.

Authors:  Luis Fernando Nicolas-Alonso; Jaime Gomez-Gil
Journal:  Sensors (Basel)       Date:  2012-01-31       Impact factor: 3.576

2.  Does the 'P300' speller depend on eye gaze?

Authors:  P Brunner; S Joshi; S Briskin; J R Wolpaw; H Bischof; G Schalk
Journal:  J Neural Eng       Date:  2010-09-21       Impact factor: 5.379

3.  A novel P300-based brain-computer interface stimulus presentation paradigm: moving beyond rows and columns.

Authors:  G Townsend; B K LaPallo; C B Boulay; D J Krusienski; G E Frye; C K Hauser; N E Schwartz; T M Vaughan; J R Wolpaw; E W Sellers
Journal:  Clin Neurophysiol       Date:  2010-03-26       Impact factor: 3.708

Review 4.  Human visual skills for brain-computer interface use: a tutorial.

Authors:  Melanie Fried-Oken; Michelle Kinsella; Betts Peters; Brandon Eddy; Bruce Wojciechowski
Journal:  Disabil Rehabil Assist Technol       Date:  2020-06-01

5.  Performance improvement of ERP-based brain-computer interface via varied geometric patterns.

Authors:  Zheng Ma; Tianshuang Qiu
Journal:  Med Biol Eng Comput       Date:  2017-06-28       Impact factor: 2.602

6.  New horizons in brain-computer interface research.

Authors:  Eric W Sellers
Journal:  Clin Neurophysiol       Date:  2012-08-16       Impact factor: 3.708

7.  A comparison study of two P300 speller paradigms for brain-computer interface.

Authors:  Jiahui Pan; Yuanqing Li; Zhenghui Gu; Zhuliang Yu
Journal:  Cogn Neurodyn       Date:  2013-04-16       Impact factor: 5.082

8.  Evaluating brain-computer interface performance using color in the P300 checkerboard speller.

Authors:  D B Ryan; G Townsend; N A Gates; K Colwell; E W Sellers
Journal:  Clin Neurophysiol       Date:  2017-08-08       Impact factor: 3.708

9.  Bayesian approach to dynamically controlling data collection in P300 spellers.

Authors:  Chandra S Throckmorton; Kenneth A Colwell; David B Ryan; Eric W Sellers; Leslie M Collins
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2013-03-21       Impact factor: 3.802

10.  A general P300 brain-computer interface presentation paradigm based on performance guided constraints.

Authors:  George Townsend; Jessica Shanahan; David B Ryan; Eric W Sellers
Journal:  Neurosci Lett       Date:  2012-08-29       Impact factor: 3.046

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.