Korik, Attila;
Du Bois, Naomi;
Campbell, Gerard;
O'Neill, Eamonn;
Hay, Laura;
Gilbert, Sam;
Grealy, Madeleine;
(2024)
Real-time feedback improves imagined 3D primitive object classification from EEG.
Brain-Computer Interfaces
10.1080/2326263X.2024.2334558.
(In press).
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Abstract
Brain-computer interfaces (BCI) enable movement-independent information transfer from humans to computers. Decoding imagined 3D objects from electroencephalography (EEG) may improve design ideation in engineering design or image reconstruction from EEG for application in brain-computer interfaces, neuro-prosthetics, and cognitive neuroscience research. Object-imagery decoding studies, to date, predominantly employ functional magnetic resonance imaging (fMRI) and do not provide real-time feedback. We present four linked studies in a study series to investigate: (1) whether five imagined 3D primitive objects (sphere, cone, pyramid, cylinder, and cube) could be decoded from EEG; and (2) the influence of real-time feedback on decoding accuracy. Studies 1 (N = 10) and 2 (N = 3) involved a single-session and a multi-session design, respectively, without real-time feedback. Studies 3 (N = 2) and 4 (N = 4) involved multiple sessions, without and with real-time feedback. The four studies involved 69 sessions in total of which 26 sessions were online with real-time feedback (15,480 trials for offline and at least 6,840 trials for online sessions in total). We demonstrate that decoding accuracy over multiple sessions improves significantly with biased feedback (p = 0.004), compared to performance without feedback. This is the first study to show the effect of real-time feedback on the performance of primitive object-imagery BCI.
| Type: | Article |
|---|---|
| Title: | Real-time feedback improves imagined 3D primitive object classification from EEG |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/2326263X.2024.2334558 |
| Publisher version: | http://dx.doi.org/10.1080/2326263x.2024.2334558 |
| Language: | English |
| Additional information: | Copyright © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. 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 work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. |
| Keywords: | Brain-computer interface (BCI); imagined 3D objects; real-time signal processing; filter-bank common spatial patterns (FBCSP); electroencephalography (EEG) |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Institute of Cognitive Neuroscience |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10191251 |
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