Using Hybrid Feature and Classifier Fusion for an Asynchronous Brain–Computer Interface Framework Based on Steady-State Motion Visual Evoked Potentials

This study proposes an asynchronous brain–computer interface (BCI) framework based on steady-state motion visual evoked potentials (SSMVEPs), designed to enhance the accuracy and robustness of control state recognition. The method integrates filter bank common spatial patterns (FBCSPs) and filter ba...

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Detalhes bibliográficos

Principais autores:	Bo Hu, Jun Xie, Huanqing Zhang, Junjie Liu, Hu Wang
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2025-05-01
coleção:	Applied Sciences
Assuntos:	asynchronous BCI SSMVEP feature fusion ensemble classification
Acesso em linha:	https://www.mdpi.com/2076-3417/15/11/6010
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