A hybrid brain-computer interface using motor imagery and SSVEP Based on convolutional neural network

A hybrid brain-computer interface using motor imagery and SSVEP Based on convolutional neural network

The key to electroencephalography (EEG)-based brain-computer interface (BCI) lies in neural decoding, and its accuracy can be improved by using hybrid BCI paradigms, that is, fusing multiple paradigms. However, hybrid BCIs usually require separate processing processes for EEG signals in each paradig...

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Bibliographic Details
Main Authors: Wenwei Luo, Wanguang Yin, Quanying Liu, Youzhi Qu
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:Brain-Apparatus Communication
Subjects:
brain-computer interface (bci)
convolutional neural networks (cnns)
electroencephalography (eeg)
steady-state visual evoked potential (ssvep)
motor imagery (mi)
Online Access:http://dx.doi.org/10.1080/27706710.2023.2258938

Internet

http://dx.doi.org/10.1080/27706710.2023.2258938

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