PRISM: Deep metric learning based personal grouping method to reduce intersubject variability for motor imagery brain–computer interface-Reference-Cited by-同舟云学术

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PRISM: Deep metric learning based personal grouping method to reduce intersubject variability for motor imagery brain–computer interface

Published:2024-08 Issue: Volume:593 Page:127805
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Kim Kyungdo^ORCID,Kim Kwangsoo^ORCID,Lee Seung-Bo^ORCID

Funder

Seoul National University Hospital

Publisher

Elsevier BV

Reference85 articles.

1. A review of critical challenges in MI-BCI: from conventional to deep learning methods;Khademi;J. Neurosci. Methods,2023

2. A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers;Zhang;J. Neuroeng.,2021

3. Signal processing techniques for motor imagery brain computer interface: A review;Aggarwal;Array,2019

4. Brain-computer interfaces in medicine;Shih,2012

5. Adaptive asynchronous control system of robotic arm based on augmented reality-assisted brain–computer interface;Chen;J. Neural Eng.,2021

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