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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Autores principales:	Wenwei Luo, Wanguang Yin, Quanying Liu, Youzhi Qu
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Taylor & Francis Group 2023-12-01
Colección:	Brain-Apparatus Communication
Materias:	brain-computer interface (bci) convolutional neural networks (cnns) electroencephalography (eeg) steady-state visual evoked potential (ssvep) motor imagery (mi)
Acceso en línea:	http://dx.doi.org/10.1080/27706710.2023.2258938
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