Literature DB >> 20573542

Customized stimulation enhances performance of independent binary SSVEP-BCIs.

M A Lopez-Gordo1, A Prieto, F Pelayo, C Morillas.   

Abstract

OBJECTIVE: Brain-computer interfaces based on steady-state visual evoked potentials (SSVEP-BCIs) achieve the highest performance, due to their multiclass nature, in paradigms in which different visual stimuli are shown. Studies of independent binary SSVEP-BCIs have been previously presented in which it was not necessary to gaze at the stimuli at the cost of performance. Despite that, the energy of the SSVEPs is largely affected by the temporal and spatial frequencies of the stimulus, there are no studies in the BCI literature about its combined impact on the final performance of SSVEP-BCIs. The objective of this study is to present an experiment that evaluates the best configuration of the visual stimulus for each subject, thus minimizing the decline in performance of independent binary SSVEP-BCIs.
METHODS: The participants attended and ignored a single structured stimulus configured with a combination of spatial and temporal frequencies at a time. They were instructed to gaze at a central point during the whole experiment. The best combination of spatial and temporal frequencies achieved for each subject, in terms of signal-to-noise ratio (SNR), was subsequently determined.
RESULTS: The SNR showed a significant dependency on the combination of frequencies, in such a way that only a reduced set of these combinations was applicable for obtaining an optimum SNR. The selection of an inappropriate stimulus configuration may cause a degradation of the information transmission rate (ITR) as it does the SNR.
CONCLUSIONS: The appropriate selection of the optimal spatial and temporal frequencies determines the performance of independent binary SSVEP-BCIs. This fact is critical to enhance its low performance; hence, they should be adjusted independently for each subject. SIGNIFICANCE: Independent binary SSVEP-BCIs can be used in patients who are unable to control their gaze sufficiently. The correct selection of the spatial and temporal frequencies has a considerable benefit on their low ITR that must be taken into account. In order to find the most suitable frequencies, a test similar to the presented in this study should be performed beforehand for each SSVEP-BCI user. This regard is not documented in studies conducted in the BCI literature.
Copyright © 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

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Year:  2010        PMID: 20573542     DOI: 10.1016/j.clinph.2010.05.021

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


  7 in total

1.  Exploiting individual primary visual cortex geometry to boost steady state visual evoked potentials.

Authors:  M Isabel Vanegas; Annabelle Blangero; Simon P Kelly
Journal:  J Neural Eng       Date:  2013-04-03       Impact factor: 5.379

2.  Assisted closed-loop optimization of SSVEP-BCI efficiency.

Authors:  Jacobo Fernandez-Vargas; Hanns U Pfaff; Francisco B Rodríguez; Pablo Varona
Journal:  Front Neural Circuits       Date:  2013-02-25       Impact factor: 3.492

3.  Real-time decoding of brain responses to visuospatial attention using 7T fMRI.

Authors:  Patrik Andersson; Josien P W Pluim; Jeroen C W Siero; Stefan Klein; Max A Viergever; Nick F Ramsey
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4.  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

5.  A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI.

Authors:  Piotr Stawicki; Felix Gembler; Aya Rezeika; Ivan Volosyak
Journal:  Brain Sci       Date:  2017-04-05

6.  Objective evaluation of fatigue by EEG spectral analysis in steady-state visual evoked potential-based brain-computer interfaces.

Authors:  Teng Cao; Feng Wan; Chi Man Wong; Janir Nuno da Cruz; Yong Hu
Journal:  Biomed Eng Online       Date:  2014-03-12       Impact factor: 2.819

7.  Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface.

Authors:  Bor-Shyh Lin; Bor-Shing Lin; Tzu-Hsiang Yen; Chien-Chin Hsu; Yao-Chin Wang
Journal:  Micromachines (Basel)       Date:  2019-10-10       Impact factor: 2.891

  7 in total

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