Literature DB >> 24058009

A speedy hybrid BCI spelling approach combining P300 and SSVEP.

Erwei Yin, Zongtan Zhou, Jun Jiang, Fanglin Chen, Yadong Liu, Dewen Hu.   

Abstract

This study proposes a novel hybrid brain-computer interface (BCI) approach for increasing the spelling speed. In this approach, the P300 and steady-state visually evoked potential (SSVEP) detection mechanisms are devised and integrated so that the two brain signals can be used for spelling simultaneously. Specifically, the target item is identified by 2-D coordinates that are realized by the two brain patterns. The subarea/location and row/column speedy spelling paradigms were designed based on this approach. The results obtained for 14 healthy subjects demonstrate that the average online practical information transfer rate, including the time of break between selections and error correcting, achieved using our approach was 53.06 bits/min. The pilot studies suggest that our BCI approach could achieve higher spelling speed compared with the conventional P300 and SSVEP spellers.

Mesh:

Year:  2014        PMID: 24058009     DOI: 10.1109/TBME.2013.2281976

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


  23 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.  Incorporating advanced language models into the P300 speller using particle filtering.

Authors:  W Speier; C W Arnold; A Deshpande; J Knall; N Pouratian
Journal:  J Neural Eng       Date:  2015-06-10       Impact factor: 5.379

3.  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

4.  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 5.  Review of brain encoding and decoding mechanisms for EEG-based brain-computer interface.

Authors:  Lichao Xu; Minpeng Xu; Tzyy-Ping Jung; Dong Ming
Journal:  Cogn Neurodyn       Date:  2021-04-10       Impact factor: 3.473

6.  Multi-phase cycle coding for SSVEP based brain-computer interfaces.

Authors:  Jijun Tong; Danhua Zhu
Journal:  Biomed Eng Online       Date:  2015-01-16       Impact factor: 2.819

7.  Simultaneous detection of P300 and steady-state visually evoked potentials for hybrid brain-computer interface.

Authors:  Adrien Combaz; Marc M Van Hulle
Journal:  PLoS One       Date:  2015-03-27       Impact factor: 3.240

8.  A Wearable Channel Selection-Based Brain-Computer Interface for Motor Imagery Detection.

Authors:  Chi-Chun Lo; Tsung-Yi Chien; Yu-Chun Chen; Shang-Ho Tsai; Wai-Chi Fang; Bor-Shyh Lin
Journal:  Sensors (Basel)       Date:  2016-02-06       Impact factor: 3.576

9.  A Gaze Independent Brain-Computer Interface Based on Visual Stimulation through Closed Eyelids.

Authors:  Han-Jeong Hwang; Valeria Y Ferreria; Daniel Ulrich; Tayfun Kilic; Xenofon Chatziliadis; Benjamin Blankertz; Matthias Treder
Journal:  Sci Rep       Date:  2015-10-29       Impact factor: 4.379

10.  Optimizing the Face Paradigm of BCI System by Modified Mismatch Negative Paradigm.

Authors:  Sijie Zhou; Jing Jin; Ian Daly; Xingyu Wang; Andrzej Cichocki
Journal:  Front Neurosci       Date:  2016-10-07       Impact factor: 4.677

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