A survey of deep learning-based classification methods for steady-state visual evoked potentials-Reference-Cited by-同舟云学术

A survey of deep learning-based classification methods for steady-state visual evoked potentials

Published:2023-03-03 Issue:1 Volume:2 Page:
ISSN:2770-6710
Container-title:Brain-Apparatus Communication: A Journal of Bacomics
language:en
Short-container-title:Brain-Apparatus Communication: A Journal of Bacomics

Author:

Pan Yudong¹^ORCID,Chen Jianbo¹^ORCID,Zhang Yangsong¹²^ORCID

Affiliation:

1. School of Computer Science and Technology, Laboratory for Brain Science and Medical Artificial Intelligence, Southwest University of Science and Technology, Mianyang, P.R. China

2. MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, P.R. China

Funder

National Natural Science Foundation

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/27706710.2023.2181102

Reference93 articles.

1. Brain–computer interfaces for communication and control

2. From psychosomatic medicine, brain–computer interface to brain–apparatus communication

3. Brain-computer interfaces (BCIs) for communication and control

4. RSTFC: A Novel Algorithm for Spatio-Temporal Filtering and Classification of Single-Trial EEG

5. An improved P300 pattern in BCI to catch user’s attention

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