Literature DB >> 23204263

P300-based brain-neuronal computer interaction for spelling applications.

C-C Postelnicu1, D Talaba.   

Abstract

A brain-neuronal computer interaction system can provide a communication channel for severely disabled people or a supplementary control channel for able-bodied subjects. In this paper, a physiological hybrid P300-based speller that uses a modified stimulus presentation paradigm-the half checkerboard paradigm (HCBP)-is evaluated. The speller uses electrooculography and electroencephalography signals for selecting alphanumeric characters or commands arranged in an 8 × 9 matrix. In this study a group of subjects, who can voluntarily gaze at a target, used the checkerboard paradigm- and HCBP-based spellers in a counterbalanced fashion for comparing their performances under a series of online tests. A 16-character-long text was spelled by each subject, while a 13-character-long text was used for calibrating the system. By using the HCBP, the time required for spelling one character is reduced, resulting in higher information transfer rates. The results suggest that the HCBP has the potential to provide a more effective P300 paradigm with a major importance for people with neuromuscular diseases and also for healthy people as a supplementary communication channel.

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Mesh:

Year:  2012        PMID: 23204263     DOI: 10.1109/TBME.2012.2228645

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  9 in total

1.  EEG Source Imaging Enhances the Decoding of Complex Right-Hand Motor Imagery Tasks.

Authors:  Bradley J Edelman; Bryan Baxter; Bin He
Journal:  IEEE Trans Biomed Eng       Date:  2015-08-12       Impact factor: 4.538

2.  Noninvasive Brain-Computer Interfaces Based on Sensorimotor Rhythms.

Authors:  Bin He; Bryan Baxter; Bradley J Edelman; Christopher C Cline; Wendy Ye
Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2015-05-20       Impact factor: 10.961

Review 3.  EEG-EOG based Virtual Keyboard: Toward Hybrid Brain Computer Interface.

Authors:  Sarah M Hosni; Howida A Shedeed; Mai S Mabrouk; Mohamed F Tolba
Journal:  Neuroinformatics       Date:  2019-07

4.  Automatic and direct identification of blink components from scalp EEG.

Authors:  Wanzeng Kong; Zhanpeng Zhou; Sanqing Hu; Jianhai Zhang; Fabio Babiloni; Guojun Dai
Journal:  Sensors (Basel)       Date:  2013-08-16       Impact factor: 3.576

5.  A supplementary system for a brain-machine interface based on jaw artifacts for the bidimensional control of a robotic arm.

Authors:  Álvaro Costa; Enrique Hortal; Eduardo Iáñez; José M Azorín
Journal:  PLoS One       Date:  2014-11-12       Impact factor: 3.240

6.  A novel channel selection method for optimal classification in different motor imagery BCI paradigms.

Authors:  Haijun Shan; Haojie Xu; Shanan Zhu; Bin He
Journal:  Biomed Eng Online       Date:  2015-10-21       Impact factor: 2.819

Review 7.  A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives.

Authors:  Inchul Choi; Ilsun Rhiu; Yushin Lee; Myung Hwan Yun; Chang S Nam
Journal:  PLoS One       Date:  2017-04-28       Impact factor: 3.240

8.  Analysis of User Interaction with a Brain-Computer Interface Based on Steady-State Visually Evoked Potentials: Case Study of a Game.

Authors:  Harlei Miguel de Arruda Leite; Sarah Negreiros de Carvalho; Thiago Bulhões da Silva Costa; Romis Attux; Heiko Horst Hornung; Dalton Soares Arantes
Journal:  Comput Intell Neurosci       Date:  2018-04-15

Review 9.  Brain-Computer Interface Spellers: A Review.

Authors:  Aya Rezeika; Mihaly Benda; Piotr Stawicki; Felix Gembler; Abdul Saboor; Ivan Volosyak
Journal:  Brain Sci       Date:  2018-03-30
  9 in total

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