Formulation of common spatial patterns for multi-task hyperscanning BCI

Falcon-Caro, A ORCID: https://orcid.org/0000-0002-1085-7716, Shirani, S ORCID: https://orcid.org/0000-0002-4188-5920, Ferreira, JF ORCID: https://orcid.org/0000-0002-2510-2412, Bird, JJ ORCID: https://orcid.org/0000-0002-9858-1231 and Sanei, S ORCID: https://orcid.org/0000-0002-3437-2801, 2024. Formulation of common spatial patterns for multi-task hyperscanning BCI. IEEE Transactions on Biomedical Engineering. ISSN 0018-9294

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Abstract

This work proposes a new formulation for common spatial patterns (CSP), often used as a powerful feature extraction technique in brain-computer interfacing (BCI) and other neurological studies. In this approach, applied to multiple subjects' data and named as hyperCSP, the individual covariance and mutual correlation matrices between multiple simultaneously recorded subjects' electroencephalograms are exploited in the CSP formulation. This method aims at effectively isolating the common motor task between multiple heads and alleviate the effects of other spurious or undesired tasks inherently or intentionally performed by the subjects. This technique can provide a satisfactory classification performance while using small data size and low computational complexity. By using the proposed hyperCSP followed by support vector machines classifier, we obtained a classification accuracy of 81.82% over 8 trials in the presence of strong undesired tasks. We hope that this method could reduce the training error in multi-task BCI scenarios. The recorded valuable motor-related hyperscanning dataset is available for public use to promote the research in this area.

Item Type:	Journal article
Publication Title:	IEEE Transactions on Biomedical Engineering
Creators:	Falcon-Caro, A., Shirani, S., Ferreira, J.F., Bird, J.J. and Sanei, S.
Publisher:	Institute of Electrical and Electronics Engineers (IEEE)
Date:	22 January 2024
ISSN:	0018-9294
Identifiers:	Number Type 10.1109/tbme.2024.3356665 DOI 1863758 Other
Rights:	© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Divisions:	Schools > School of Science and Technology
Record created by:	Laura Ward
Date Added:	21 Feb 2024 09:28
Last Modified:	12 Jul 2024 10:57
Related URLs:	Dataset used by this publication
URI:	https://irep.ntu.ac.uk/id/eprint/50898

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