EEGNet With Ensemble Learning to Improve the Cross-Session Classification of SSVEP Based BCI From Ear-EEG

EEGNet With Ensemble Learning to Improve the Cross-Session Classification of SSVEP Based BCI From Ear-EEG

Ear-electroencephalography (ear-EEG) using electrodes placed above hairless areas around ears is a convenient and comfortable method for signal recording in practical applications of steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI). However, due to the constraint of...

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Bibliographic Details
Main Authors: Yuanlu Zhu, Ying Li, Jinling Lu, Pengcheng Li
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Brain-computer interface (BCI)
convolutional neural network (CNN)
ear-electroencephalography (ear-EEG)
steady-state visual evoked potential (SSVEP)
Online Access:https://ieeexplore.ieee.org/document/9328251/

Internet

https://ieeexplore.ieee.org/document/9328251/

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