Component-mixing strategy: A decomposition-based data augmentation algorithm for motor imagery signals

Deep learning has achieved a remarkable success in areas such as brain-computer interface systems (BCI). However, electroencephalography (EEG) signals evoked by motor imagery (MI) are sometimes limited in their amount due to invalid data caused by the subjects’ fatigue, leading to a performance degr...

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Veröffentlicht in:	Neurocomputing (Amsterdam) Jg. 465; S. 325 - 335
Hauptverfasser:	Li, Binghua, Zhang, Zhiwen, Duan, Feng, Yang, Zhenglu, Zhao, Qibin, Sun, Zhe, Solé-Casals, Jordi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 20.11.2021
Schlagworte:	Brain-computer interface Data augmentation Motor imagery Signal decomposition Brain-computer interface Data augmentation Motor imagery Signal decomposition
ISSN:	0925-2312, 1872-8286
Online-Zugang:	Volltext
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