Data augmentation for self-paced motor imagery classification with C-LSTM

Objective. Brain-computer interfaces (BCI) are becoming important tools for assistive technology, particularly through the use of motor imagery (MI) for aiding task completion. However, most existing methods of MI classification have been applied in a trial-wise fashion, with window sizes of approxi...

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Veröffentlicht in:	Journal of neural engineering Jg. 17; H. 1; S. 016041 - 16055
Hauptverfasser:	Freer, Daniel, Yang, Guang-Zhong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England IOP Publishing 31.01.2020
Schlagworte:	brain-computer interface Brain-Computer Interfaces - classification data augmentation Data Science - classification Data Science - methods deep learning electroencephalography Humans Imagination - physiology Motor Cortex - physiology motor imagery Movement - physiology
ISSN:	1741-2560, 1741-2552, 1741-2552
Online-Zugang:	Volltext
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