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Autonomous Parameter Adjustment for SSVEP-Based BCIs with a Novel BCI Wizard
Brain-Computer Interfaces (BCIs) transfer human brain activities into computer commands and enable a communication channel without requiring movement. Among other BCI approaches, steady-state visual evoked potential (SSVEP)-based BCIs have the potential to become accurate, assistive technologies for...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4686729/ https://www.ncbi.nlm.nih.gov/pubmed/26733788 http://dx.doi.org/10.3389/fnins.2015.00474 |
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author | Gembler, Felix Stawicki, Piotr Volosyak, Ivan |
author_facet | Gembler, Felix Stawicki, Piotr Volosyak, Ivan |
author_sort | Gembler, Felix |
collection | PubMed |
description | Brain-Computer Interfaces (BCIs) transfer human brain activities into computer commands and enable a communication channel without requiring movement. Among other BCI approaches, steady-state visual evoked potential (SSVEP)-based BCIs have the potential to become accurate, assistive technologies for persons with severe disabilities. Those systems require customization of different kinds of parameters (e.g., stimulation frequencies). Calibration usually requires selecting predefined parameters by experienced/trained personnel, though in real-life scenarios an interface allowing people with no experience in programming to set up the BCI would be desirable. Another occurring problem regarding BCI performance is BCI illiteracy (also called BCI deficiency). Many articles reported that BCI control could not be achieved by a non-negligible number of users. In order to bypass those problems we developed a SSVEP-BCI wizard, a system that automatically determines user-dependent key-parameters to customize SSVEP-based BCI systems. This wizard was tested and evaluated with 61 healthy subjects. All subjects were asked to spell the phrase “RHINE WAAL UNIVERSITY” with a spelling application after key parameters were determined by the wizard. Results show that all subjects were able to control the spelling application. A mean (SD) accuracy of 97.14 (3.73)% was reached (all subjects reached an accuracy above 85% and 25 subjects even reached 100% accuracy). |
format | Online Article Text |
id | pubmed-4686729 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-46867292016-01-05 Autonomous Parameter Adjustment for SSVEP-Based BCIs with a Novel BCI Wizard Gembler, Felix Stawicki, Piotr Volosyak, Ivan Front Neurosci Neuroscience Brain-Computer Interfaces (BCIs) transfer human brain activities into computer commands and enable a communication channel without requiring movement. Among other BCI approaches, steady-state visual evoked potential (SSVEP)-based BCIs have the potential to become accurate, assistive technologies for persons with severe disabilities. Those systems require customization of different kinds of parameters (e.g., stimulation frequencies). Calibration usually requires selecting predefined parameters by experienced/trained personnel, though in real-life scenarios an interface allowing people with no experience in programming to set up the BCI would be desirable. Another occurring problem regarding BCI performance is BCI illiteracy (also called BCI deficiency). Many articles reported that BCI control could not be achieved by a non-negligible number of users. In order to bypass those problems we developed a SSVEP-BCI wizard, a system that automatically determines user-dependent key-parameters to customize SSVEP-based BCI systems. This wizard was tested and evaluated with 61 healthy subjects. All subjects were asked to spell the phrase “RHINE WAAL UNIVERSITY” with a spelling application after key parameters were determined by the wizard. Results show that all subjects were able to control the spelling application. A mean (SD) accuracy of 97.14 (3.73)% was reached (all subjects reached an accuracy above 85% and 25 subjects even reached 100% accuracy). Frontiers Media S.A. 2015-12-22 /pmc/articles/PMC4686729/ /pubmed/26733788 http://dx.doi.org/10.3389/fnins.2015.00474 Text en Copyright © 2015 Gembler, Stawicki and Volosyak. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Gembler, Felix Stawicki, Piotr Volosyak, Ivan Autonomous Parameter Adjustment for SSVEP-Based BCIs with a Novel BCI Wizard |
title | Autonomous Parameter Adjustment for SSVEP-Based BCIs with a Novel BCI Wizard |
title_full | Autonomous Parameter Adjustment for SSVEP-Based BCIs with a Novel BCI Wizard |
title_fullStr | Autonomous Parameter Adjustment for SSVEP-Based BCIs with a Novel BCI Wizard |
title_full_unstemmed | Autonomous Parameter Adjustment for SSVEP-Based BCIs with a Novel BCI Wizard |
title_short | Autonomous Parameter Adjustment for SSVEP-Based BCIs with a Novel BCI Wizard |
title_sort | autonomous parameter adjustment for ssvep-based bcis with a novel bci wizard |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4686729/ https://www.ncbi.nlm.nih.gov/pubmed/26733788 http://dx.doi.org/10.3389/fnins.2015.00474 |
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