Data Augmentation for Motor Imagery Signal Classification Based on a Hybrid Neural Network

As an important paradigm of spontaneous brain-computer interfaces (BCIs), motor imagery (MI) has been widely used in the fields of neurological rehabilitation and robot control. Recently, researchers have proposed various methods for feature extraction and classification based on MI signals. The dec...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 20; no. 16; p. 4485
Main Authors:	Zhang, Kai, Xu, Guanghua, Han, Zezhen, Ma, Kaiquan, Zheng, Xiaowei, Chen, Longting, Duan, Nan, Zhang, Sicong
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 11.08.2020 MDPI
Subjects:	Algorithms Brain-Computer Interfaces Classification CNN data augmentation Datasets DCGAN Electroencephalography Humans Imagination Methods motor imagery Neural networks Neural Networks, Computer Noise Signal processing DCGAN motor imagery CNN data augmentation classification
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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