Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 11
3306-3309

Research on emotion recognition based on EEG signals

Zhang Jiarui
Wang Gang
College of Air & Missile Defense, Air Force Engineering University, Xi'an 710051, China
DOI: 10.19734/j.issn.1001-3695.2018.05.0295

Abstract

The relationship between EEG and emotion recognition has attracted wide attention, however, the partial accuracy of emotion recognition is low. For improving the accuracy rate, after filtered the original EEG signal to 5 bands, this paper then extracted 4 features, the differential entropy, power spectral density, wavelet entropy and approximate entropy. Finally it selected the features and used the support vector machine, K-nearest neighbor, naive Bayesian model and multi-layer perceptron for classification learning. It trained DE feature to get the higher accuracy with 4 different electrode placement methods by support vector machine. The results show that the accuracy rate reaches 91.99% of all EEG band energy in the case of 12 channels, and gets the average accuracies up to 97.59% with SVM that using genetic algorithm to acquire the optimization parameters.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.05.0295
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 11
Section: Algorithm Research & Explore
Pages: 3306-3309
Serial Number: 1001-3695(2019)11-024-3306-04

Publish History

[2019-11-05] Printed Article

Cite This Article

张家瑞, 王刚. 基于脑电信号的情感识别研究 [J]. 计算机应用研究, 2019, 36 (11): 3306-3309. (Zhang Jiarui, Wang Gang. Research on emotion recognition based on EEG signals [J]. Application Research of Computers, 2019, 36 (11): 3306-3309. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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