Literature DB >> 22580222

Development of an SSVEP-based BCI spelling system adopting a QWERTY-style LED keyboard.

Han-Jeong Hwang1, Jeong-Hwan Lim, Young-Jin Jung, Han Choi, Sang Woo Lee, Chang-Hwan Im.   

Abstract

In this study, we introduce a new mental spelling system based on steady-state visual evoked potential (SSVEP), adopting a QWERTY style layout keyboard with 30 LEDs flickering with different frequencies. The proposed electroencephalography (EEG)-based mental spelling system allows the users to spell one target character per each target selection, without the need for multiple step selections adopted by conventional SSVEP-based mental spelling systems. Through preliminary offline experiments and online experiments, we confirmed that human SSVEPs elicited by visual flickering stimuli with a frequency resolution of 0.1 Hz could be classified with classification accuracy high enough to be used for a practical brain-computer interface (BCI) system. During the preliminary offline experiments performed with five participants, we optimized various factors influencing the performance of the mental spelling system, such as distances between adjacent keys, light source arrangements, stimulating frequencies, recording electrodes, and visual angles. Additional online experiments were conducted with six participants to verify the feasibility of the optimized mental spelling system. The results of the online experiments were an average typing speed of 9.39 letters per minute (LPM) with an average success rate of 87.58%, corresponding to an average information transfer rate of 40.72 bits per minute, demonstrating the high performance of the developed mental spelling system. Indeed, the average typing speed of 9.39 LPM attained in this study was one of the best LPM results among those reported in previous BCI literatures.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 22580222     DOI: 10.1016/j.jneumeth.2012.04.011

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  37 in total

1.  A multi-day and multi-band dataset for a steady-state visual-evoked potential-based brain-computer interface.

Authors:  Ga-Young Choi; Chang-Hee Han; Young-Jin Jung; Han-Jeong Hwang
Journal:  Gigascience       Date:  2019-11-01       Impact factor: 6.524

2.  EEG-based hybrid QWERTY mental speller with high information transfer rate.

Authors:  Er Akshay Katyal; Rajesh Singla
Journal:  Med Biol Eng Comput       Date:  2021-02-16       Impact factor: 2.602

3.  High performance communication by people with paralysis using an intracortical brain-computer interface.

Authors:  Chethan Pandarinath; Paul Nuyujukian; Christine H Blabe; Brittany L Sorice; Jad Saab; Francis R Willett; Leigh R Hochberg; Krishna V Shenoy; Jaimie M Henderson
Journal:  Elife       Date:  2017-02-21       Impact factor: 8.140

4.  Recursive Bayesian Coding for BCIs.

Authors:  Matt Higger; Fernando Quivira; Murat Akcakaya; Mohammad Moghadamfalahi; Hooman Nezamfar; Mujdat Cetin; Deniz Erdogmus
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2016-07-13       Impact factor: 3.802

5.  Novel hold-release functionality in a P300 brain-computer interface.

Authors:  R E Alcaide-Aguirre; J E Huggins
Journal:  J Neural Eng       Date:  2014-11-07       Impact factor: 5.379

6.  Exploring Cognitive Flexibility With a Noninvasive BCI Using Simultaneous Steady-State Visual Evoked Potentials and Sensorimotor Rhythms.

Authors:  Bradley J Edelman; Jianjun Meng; Nicholas Gulachek; Christopher C Cline; Bin He
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2018-05       Impact factor: 3.802

7.  Behind the Scenes of Noninvasive Brain-Computer Interfaces: A Review of Electroencephalography Signals, How They Are Recorded, and Why They Matter.

Authors:  Kevin M Pitt; Jonathan S Brumberg; Jeremy D Burnison; Jyutika Mehta; Juhi Kidwai
Journal:  Perspect ASHA Spec Interest Groups       Date:  2019-11-09

8.  Playing 20 Questions with the Mind: Collaborative Problem Solving by Humans Using a Brain-to-Brain Interface.

Authors:  Andrea Stocco; Chantel S Prat; Darby M Losey; Jeneva A Cronin; Joseph Wu; Justin A Abernethy; Rajesh P N Rao
Journal:  PLoS One       Date:  2015-09-23       Impact factor: 3.240

9.  On the quantification of SSVEP frequency responses in human EEG in realistic BCI conditions.

Authors:  Rafał Kuś; Anna Duszyk; Piotr Milanowski; Maciej Łabęcki; Maria Bierzyńska; Zofia Radzikowska; Magdalena Michalska; Jarosław Zygierewicz; Piotr Suffczyński; Piotr Jerzy Durka
Journal:  PLoS One       Date:  2013-10-18       Impact factor: 3.240

10.  SSVEP extraction based on the similarity of background EEG.

Authors:  Zhenghua Wu
Journal:  PLoS One       Date:  2014-04-07       Impact factor: 3.240

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