EEGSym: Overcoming Inter-Subject Variability in Motor Imagery Based BCIs With Deep Learning-Reference-Cited by-同舟云学术

EEGSym: Overcoming Inter-Subject Variability in Motor Imagery Based BCIs With Deep Learning

Published:2022 Issue: Volume:30 Page:1766-1775
ISSN:1534-4320
Container-title:IEEE Transactions on Neural Systems and Rehabilitation Engineering
language:
Short-container-title:IEEE Trans. Neural Syst. Rehabil. Eng.

Author:

Perez-Velasco Sergio¹^ORCID,Santamaria-Vazquez Eduardo¹^ORCID,Martinez-Cagigal Victor¹^ORCID,Marcos-Martinez Diego¹^ORCID,Hornero Roberto¹^ORCID

Affiliation:

1. Biomedical Engineering Group (GIB), E.T.S Ingenieros de Telecomunicación, University of Valladolid, Valladolid, Spain

Funder

‘Ministerio de Ciencia e Innovación/Agencia Estatal de Investigación’ and European Regional Development Fund (ERDF) ‘A way of making Europe’

European Commission and ERDF through the R+D+i Project ‘Análisis y Correlación Entre la Epigenética y la Actividad Cerebral Para Evaluar el Riesgo de Migraña Crónica y Episódica en Mujeres’

CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III

Instituto de Salud Carlos III

Sergio Pérez-Velasco, Eduardo Santamaría-Vázquez, and Diego Marcos-Martínez

PIF Grant from the ’Consejería de educación de la Junta de Castilla y León

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation

Link

http://xplorestaging.ieee.org/ielx7/7333/9695946/09807323.pdf?arnumber=9807323

Reference49 articles.

1. Mindfulness Improves Brain–Computer Interface Performance by Increasing Control Over Neural Activity in the Alpha Band

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4. Thinker invariance: enabling deep neural networks for BCI across more people

5. Attention is all you need;vaswani;Proc Adv Neural Inf Process Syst (NIPS),2017

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