EEG Classification of Motor Imagery Using a Novel Deep Learning Framework

EEG Classification of Motor Imagery Using a Novel Deep Learning Framework

Successful applications of brain-computer interface (BCI) approaches to motor imagery (MI) are still limited. In this paper, we propose a classification framework for MI electroencephalogram (EEG) signals that combines a convolutional neural network (CNN) architecture with a variational autoencoder...

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Bibliographic Details
Main Authors: Mengxi Dai, Dezhi Zheng, Rui Na, Shuai Wang, Shuailei Zhang
Format: Article
Language:English
Published: MDPI AG 2019-01-01
Series:Sensors
Subjects:
EEG
deep learning
short-time Fourier transform
convolutional neural network
variational autoencoder
Online Access:https://www.mdpi.com/1424-8220/19/3/551

Internet

https://www.mdpi.com/1424-8220/19/3/551

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