Motor imagery EEG classification algorithm based on CNN-LSTM feature fusion network

•Convolutional neural network and Long Short-term Memory Network are connected in parallel to form a fusion network.•The spatial feature, temporal feature and middle layer feature are extracted and fused integrally.•The average accuracy and Kappa value of the proposed algorithm are 87.68% and 0.8245...

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Bibliographic Details

Published in:	Biomedical signal processing and control Vol. 72; p. 103342
Main Authors:	Li, Hongli, Ding, Man, Zhang, Ronghua, Xiu, Chunbo
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.02.2022
Subjects:	CNN EEG classification Feature fusion LSTM Motor Imagery Motor Imagery EEG classification CNN Feature fusion LSTM
ISSN:	1746-8094, 1746-8108
Online Access:	Get full text
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