Matran-Fernandez, Ana and Poli, Riccardo (2017) Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces. PLoS ONE, 12 (5). e0178498-e0178498. DOI https://doi.org/10.1371/journal.pone.0178498
Matran-Fernandez, Ana and Poli, Riccardo (2017) Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces. PLoS ONE, 12 (5). e0178498-e0178498. DOI https://doi.org/10.1371/journal.pone.0178498
Matran-Fernandez, Ana and Poli, Riccardo (2017) Towards the automated localisation of targets in rapid image-sifting by collaborative brain-computer interfaces. PLoS ONE, 12 (5). e0178498-e0178498. DOI https://doi.org/10.1371/journal.pone.0178498
Abstract
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.
Item Type: | Article |
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Additional Information: | The data for this publication are available at https://physionet.org/physiobank/database/ltrsvp/ |
Uncontrolled Keywords: | Humans; Photic Stimulation; Task Performance and Analysis; Evoked Potentials; Automation; Adult; Female; Male; Young Adult; Brain-Computer Interfaces |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 05 Jun 2017 14:43 |
Last Modified: | 16 May 2024 17:32 |
URI: | http://repository.essex.ac.uk/id/eprint/19743 |
Available files
Filename: journal.pone.0178498.pdf
Licence: Creative Commons: Attribution 3.0