Recognition of EEG Signal Motor Imagery Intention Based on Deep Multi-View Feature Learning

Recognition of motor imagery intention is one of the hot current research focuses of brain-computer interface (BCI) studies. It can help patients with physical dyskinesia to convey their movement intentions. In recent years, breakthroughs have been made in the research on recognition of motor imager...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Switzerland), 2020-06, Vol.20 (12), p.3496, Article 3496
Hauptverfasser:	Xu, Jiacan, Zheng, Hao, Wang, Jianhui, Li, Donglin, Fang, Xiaoke
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Brain research brain-computer interface (BCI) Brain-Computer Interfaces Chemistry Chemistry, Analytical Datasets Deep learning deep neural network Dyskinesia Electroencephalography electroencephalography (EEG) Engineering Engineering, Electrical & Electronic Feature recognition Frequency domain analysis Human-computer interface Humans Image classification Imagination Injuries Instruments & Instrumentation Intention Methods multi-view learning Neural networks parametric t-distributed stochastic neighbor embedding (p.t-SNE) Physical Sciences Science & Technology Signal processing Support vector machines Technology
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