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Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces
The N2pc is a lateralised Event-Related Potential (ERP) that signals a shift of attention towards the location of a potential object of interest. We propose a single-trial target-localisation collaborative Brain-Computer Interface (cBCI) that exploits this ERP to automatically approximate the horizo...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5451058/ https://www.ncbi.nlm.nih.gov/pubmed/28562664 http://dx.doi.org/10.1371/journal.pone.0178498 |
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author | Matran-Fernandez, Ana Poli, Riccardo |
author_facet | Matran-Fernandez, Ana Poli, Riccardo |
author_sort | Matran-Fernandez, Ana |
collection | PubMed |
description | The N2pc is a lateralised Event-Related Potential (ERP) that signals a shift of attention towards the location of a potential object of interest. We propose a single-trial target-localisation collaborative Brain-Computer Interface (cBCI) that exploits this ERP to automatically approximate the horizontal position of targets in aerial images. Images were presented by means of the rapid serial visual presentation technique at rates of 5, 6 and 10 Hz. We created three different cBCIs and tested a participant selection method in which groups are formed according to the similarity of participants’ performance. The N2pc that is elicited in our experiments contains information about the position of the target along the horizontal axis. Moreover, combining information from multiple participants provides absolute median improvements in the area under the receiver operating characteristic curve of up to 21% (for groups of size 3) with respect to single-user BCIs. These improvements are bigger when groups are formed by participants with similar individual performance, and much of this effect can be explained using simple theoretical models. Our results suggest that BCIs for automated triaging can be improved by integrating two classification systems: one devoted to target detection and another to detect the attentional shifts associated with lateral targets. |
format | Online Article Text |
id | pubmed-5451058 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-54510582017-06-12 Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces Matran-Fernandez, Ana Poli, Riccardo PLoS One Research Article The N2pc is a lateralised Event-Related Potential (ERP) that signals a shift of attention towards the location of a potential object of interest. We propose a single-trial target-localisation collaborative Brain-Computer Interface (cBCI) that exploits this ERP to automatically approximate the horizontal position of targets in aerial images. Images were presented by means of the rapid serial visual presentation technique at rates of 5, 6 and 10 Hz. We created three different cBCIs and tested a participant selection method in which groups are formed according to the similarity of participants’ performance. The N2pc that is elicited in our experiments contains information about the position of the target along the horizontal axis. Moreover, combining information from multiple participants provides absolute median improvements in the area under the receiver operating characteristic curve of up to 21% (for groups of size 3) with respect to single-user BCIs. These improvements are bigger when groups are formed by participants with similar individual performance, and much of this effect can be explained using simple theoretical models. Our results suggest that BCIs for automated triaging can be improved by integrating two classification systems: one devoted to target detection and another to detect the attentional shifts associated with lateral targets. Public Library of Science 2017-05-31 /pmc/articles/PMC5451058/ /pubmed/28562664 http://dx.doi.org/10.1371/journal.pone.0178498 Text en © 2017 Matran-Fernandez, Poli http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Matran-Fernandez, Ana Poli, Riccardo Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces |
title | Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces |
title_full | Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces |
title_fullStr | Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces |
title_full_unstemmed | Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces |
title_short | Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces |
title_sort | towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5451058/ https://www.ncbi.nlm.nih.gov/pubmed/28562664 http://dx.doi.org/10.1371/journal.pone.0178498 |
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