Multi-Objective Optimization-Based High-Pass Spatial Filtering for SSVEP-Based Brain-Computer Interfaces

Many spatial filtering methods have been proposed to enhance the target identification performance for the steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI). The existing approaches tend to learn spatial filter parameters of a certain target using only the training da...

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Veröffentlicht in:	IEEE transactions on instrumentation and measurement Jg. 71; S. 1 - 9
Hauptverfasser:	Zhang, Yue, Li, Zhenhong, Xie, Sheng Quan, Wang, He, Yu, Zhibin, Zhang, Zhi-Qiang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Brain–computer interface (BCI) Correlation Correlation analysis Datasets Electrodes Electroencephalography electroencephalography (EEG) Feature extraction high-pass spatial filter Human-computer interface multi-objective optimization Multiple objective analysis Optimization Signal to noise ratio Spatial filtering steady-state visual evoked potential (SSVEP) Target recognition Training Visualization
ISSN:	0018-9456, 1557-9662
Online-Zugang:	Volltext
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