Back to Search Start Over

Convolutional neural network based on recurrence plot for EEG recognition.

Convolutional neural network based on recurrence plot for EEG recognition.

Authors :
Hao, Chongqing
Wang, Ruiqi
Li, Mengyu
Ma, Chao
Cai, Qing
Gao, Zhongke
Source :
Chaos; Dec2021, Vol. 31 Issue 12, p1-9, 9p
Publication Year :
2021

Abstract

Electroencephalogram (EEG) is a typical physiological signal. The classification of EEG signals is of great significance to human beings. Combining recurrence plot and convolutional neural network (CNN), we develop a novel method for classifying EEG signals. We select two typical EEG signals, namely, epileptic EEG and fatigue driving EEG, to verify the effectiveness of our method. We construct recurrence plots from EEG signals. Then, we build a CNN framework to classify the EEG signals under different brain states. For the classification of epileptic EEG signals, we design three different experiments to evaluate the performance of our method. The results suggest that the proposed framework can accurately distinguish the normal state and the seizure state of epilepsy. Similarly, for the classification of fatigue driving EEG signals, the method also has a good classification accuracy. In addition, we compare with the existing methods, and the results show that our method can significantly improve the detection results. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10541500
Volume :
31
Issue :
12
Database :
Complementary Index
Journal :
Chaos
Publication Type :
Academic Journal
Accession number :
154429850
Full Text :
https://doi.org/10.1063/5.0062242