Classification of Motor Imagery EEG Signals Based on Data Augmentation and Convolutional Neural Networks

In brain–computer interface (BCI) systems, motor imagery electroencephalography (MI-EEG) signals are commonly used to detect participant intent. Many factors, including low signal-to-noise ratios and few high-quality samples, make MI classification difficult. In order for BCI systems to function, MI...

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Auteurs principaux:	Yu Xie, Stefan Oniga
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2023-02-01
Collection:	Sensors
Sujets:	motor imagery (MI) electroencephalogram (EEG) data augmentation (DA) convolutional neural network (CNN)
Accès en ligne:	https://www.mdpi.com/1424-8220/23/4/1932
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