A Novel Data Augmentation Approach Using Mask Encoding for Deep Learning-Based Asynchronous SSVEP-BCI

A Novel Data Augmentation Approach Using Mask Encoding for Deep Learning-Based Asynchronous SSVEP-BCI

Deep learning (DL)-based methods have been successfully employed as asynchronous classification algorithms in the steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) system. However, these methods often suffer from the limited amount of electroencephalography (EEG) data...

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Bibliographic Details
Main Authors: Wenlong Ding, Aiping Liu, Ling Guan, Xun Chen
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Subjects:
Asynchronous brain-computer interface
data augmentation
deep learning
electroencephalography mask encoding
steady-state visual evoked potential
Online Access:https://ieeexplore.ieee.org/document/10439237/

Internet

https://ieeexplore.ieee.org/document/10439237/

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