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...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Bo Hu, Jun Xie, Huanqing Zhang, Junjie Liu, Hu Wang
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2025-05-01
Schriftenreihe:	Applied Sciences
Schlagworte:	asynchronous BCI SSMVEP feature fusion ensemble classification
Online-Zugang:	https://www.mdpi.com/2076-3417/15/11/6010
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