Publication: MEANSP: How many channels are needed to predict the performance of a SMR-Based BCI?
| dc.contributor.author | Jorajuría, Tania | |
| dc.contributor.author | Nikulin, Vadim V. | es_ES |
| dc.contributor.author | Kapralov, Nikolai | es_ES |
| dc.contributor.author | Gómez Fernández, Marisol | |
| dc.contributor.author | Vidaurre, Carmen | |
| dc.contributor.department | Estadística, Informática y Matemáticas | es_ES |
| dc.contributor.department | Estatistika, Informatika eta Matematika | eu |
| dc.date.accessioned | 2024-05-15T16:55:16Z | |
| dc.date.available | 2024-05-15T16:55:16Z | |
| dc.date.issued | 2023 | |
| dc.date.updated | 2024-05-15T16:32:28Z | |
| dc.description.abstract | Predicting whether a particular individual would reach an adequate control of a Brain-Computer Interface (BCI) has many practical advantages. On the one hand, participants with low predicted performance could be trained with specifically designed sessions and avoid frustrating experiments; on the other hand, planning time and resources would be more efficient; and finally, the variables related to an accurate prediction could be manipulated to improve the prospective BCI performance. To this end, several predictors have been proposed in the literature, most of them based on the power estimation of EEG signals at the specific frequency bands. Many of these studies evaluate their predictors in relatively small datasets and/or using a relatively high number of channels. In this manuscript, we propose a novel predictor called MEANSP to predict the performance of participants using BCIs that are based on the modulation of sensorimotor rhythms. This novel predictor has been positively evaluated using only 2, 3, 4 or 5 channels. MEANSP has shown to perform as well as or better than other state-of-the-art predictors. The best sets of different number of channels are also provided, which have been tested in two different settings to prove their robustness. The proposed predictor has been successfully evaluated using two large-scale datasets containing 150 and 80 participants, respectively. We also discuss predictor thresholds for users to expect good performance in feedback experiments and show the advantages in comparison to a competing algorithm. | en |
| dc.description.sponsorship | This work was supported in part by the Basque Government under Grant BERC 2022-2025 and in part by the Spanish State Research Agency through Basque Center On Cognition, Brain and Language (BCBL) Severo Ochoa Excellence Accreditation under Grant CEX2020-001010/AEI/ 10.13039/501100011033. The work of Carmen Vidaurre was supported in part by the Spanish Ministry of Research and Innovation under Grant PID2020-118829RB-100, in part by Diputacion Foral de Gipuzkoa (DFG) Brain2Move Project, in part by DFG Neurocog Project, and in part by Ikerbasque. | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Jorajuría, T., Nikulin, V. V., Kapralov, N., Gómez, M., Vidaurre, C. (2023) MEANSP: How many channels are needed to predict the performance of a SMR-Based BCI?. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31, 4931-4941. https://doi.org/10.1109/TNSRE.2023.3339612. | en |
| dc.identifier.doi | 10.1109/TNSRE.2023.3339612 | |
| dc.identifier.issn | 1534-4320 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/48115 | |
| dc.language.iso | eng | en |
| dc.publisher | IEEE | en |
| dc.relation.ispartof | IEEE Transactions on Neural Systems and Rehabilitation Engineering 31, 2023, 4931-4941 | en |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI//CEX2020-001010 | en |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI//PID2020-118829RB-100 | en |
| dc.relation.publisherversion | https://doi.org/10.1109/TNSRE.2023.3339612 | |
| dc.rights | © 2023 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. | en |
| dc.rights.accessRights | Acceso abierto / Sarbide irekia | es |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | BCI inefficiency | en |
| dc.subject | Brain-computer interface (BCI) | en |
| dc.subject | Cross-frequency coupling , performance predictor , BCI inefficiency | en |
| dc.subject | Performance predictor | en |
| dc.subject | Sensorimotor rhythms (SMRs) | en |
| dc.title | MEANSP: How many channels are needed to predict the performance of a SMR-Based BCI? | en |
| dc.type | Artículo / Artikulua | es |
| dc.type | info:eu-repo/semantics/article | en |
| dc.type.version | Versión publicada / Argitaratu den bertsioa | es |
| dc.type.version | info:eu-repo/semantics/publishedVersion | en |
| dspace.entity.type | Publication | |
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