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Prediction of P300 BCI Aptitude in Severe Motor Impairment
Brain-computer interfaces (BCIs) provide a non-muscular communication channel for persons with severe motor impairments. Previous studies have shown that the aptitude with which a BCI can be controlled varies from person to person. A reliable predictor of performance could facilitate selection of a...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3799852/ https://www.ncbi.nlm.nih.gov/pubmed/24204597 http://dx.doi.org/10.1371/journal.pone.0076148 |
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author | Halder, Sebastian Ruf, Carolin Anne Furdea, Adrian Pasqualotto, Emanuele De Massari, Daniele van der Heiden, Linda Bogdan, Martin Rosenstiel, Wolfgang Birbaumer, Niels Kübler, Andrea Matuz, Tamara |
author_facet | Halder, Sebastian Ruf, Carolin Anne Furdea, Adrian Pasqualotto, Emanuele De Massari, Daniele van der Heiden, Linda Bogdan, Martin Rosenstiel, Wolfgang Birbaumer, Niels Kübler, Andrea Matuz, Tamara |
author_sort | Halder, Sebastian |
collection | PubMed |
description | Brain-computer interfaces (BCIs) provide a non-muscular communication channel for persons with severe motor impairments. Previous studies have shown that the aptitude with which a BCI can be controlled varies from person to person. A reliable predictor of performance could facilitate selection of a suitable BCI paradigm. Eleven severely motor impaired participants performed three sessions of a P300 BCI web browsing task. Before each session auditory oddball data were collected to predict the BCI aptitude of the participants exhibited in the current session. We found a strong relationship of early positive and negative potentials around 200 ms (elicited with the auditory oddball task) with performance. The amplitude of the P2 (r = −0.77) and of the N2 (r = −0.86) had the strongest correlations. Aptitude prediction using an auditory oddball was successful. The finding that the N2 amplitude is a stronger predictor of performance than P3 amplitude was reproduced after initially showing this effect with a healthy sample of BCI users. This will reduce strain on the end-users by minimizing the time needed to find suitable paradigms and inspire new approaches to improve performance. |
format | Online Article Text |
id | pubmed-3799852 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-37998522013-11-07 Prediction of P300 BCI Aptitude in Severe Motor Impairment Halder, Sebastian Ruf, Carolin Anne Furdea, Adrian Pasqualotto, Emanuele De Massari, Daniele van der Heiden, Linda Bogdan, Martin Rosenstiel, Wolfgang Birbaumer, Niels Kübler, Andrea Matuz, Tamara PLoS One Research Article Brain-computer interfaces (BCIs) provide a non-muscular communication channel for persons with severe motor impairments. Previous studies have shown that the aptitude with which a BCI can be controlled varies from person to person. A reliable predictor of performance could facilitate selection of a suitable BCI paradigm. Eleven severely motor impaired participants performed three sessions of a P300 BCI web browsing task. Before each session auditory oddball data were collected to predict the BCI aptitude of the participants exhibited in the current session. We found a strong relationship of early positive and negative potentials around 200 ms (elicited with the auditory oddball task) with performance. The amplitude of the P2 (r = −0.77) and of the N2 (r = −0.86) had the strongest correlations. Aptitude prediction using an auditory oddball was successful. The finding that the N2 amplitude is a stronger predictor of performance than P3 amplitude was reproduced after initially showing this effect with a healthy sample of BCI users. This will reduce strain on the end-users by minimizing the time needed to find suitable paradigms and inspire new approaches to improve performance. Public Library of Science 2013-10-18 /pmc/articles/PMC3799852/ /pubmed/24204597 http://dx.doi.org/10.1371/journal.pone.0076148 Text en © 2013 Halder et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Halder, Sebastian Ruf, Carolin Anne Furdea, Adrian Pasqualotto, Emanuele De Massari, Daniele van der Heiden, Linda Bogdan, Martin Rosenstiel, Wolfgang Birbaumer, Niels Kübler, Andrea Matuz, Tamara Prediction of P300 BCI Aptitude in Severe Motor Impairment |
title | Prediction of P300 BCI Aptitude in Severe Motor Impairment |
title_full | Prediction of P300 BCI Aptitude in Severe Motor Impairment |
title_fullStr | Prediction of P300 BCI Aptitude in Severe Motor Impairment |
title_full_unstemmed | Prediction of P300 BCI Aptitude in Severe Motor Impairment |
title_short | Prediction of P300 BCI Aptitude in Severe Motor Impairment |
title_sort | prediction of p300 bci aptitude in severe motor impairment |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3799852/ https://www.ncbi.nlm.nih.gov/pubmed/24204597 http://dx.doi.org/10.1371/journal.pone.0076148 |
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