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Detection methamphetamine patients using ERP features

Authors :
Junfeng Gao
Yijun Xiong
Jiaqi Zhang
Source :
2019 6th International Conference on Information Science and Control Engineering (ICISCE).
Publication Year :
2019
Publisher :
IEEE, 2019.

Abstract

Drug abuse can make people appear mental excitement and other symptoms, among which the damage to the brain is particularly serious. As a new kind of drug, methamphetamine (meth) spreads rapidly among people, and its number of users has ranked second in the world. In recent years, more and more studies have been conducted on meth users using EEG signals. However, most of the current studies have only performed ERP analysis and psychological tests on meth patients. In this study, 40 subjects were asked to receive specific stimuli and give correct feedback, and their EEG signals were recorded in the process. Statistical analysis showed that the differences in the extracted features between the two groups were significant. The electrode pairs with significant difference between the two groups were selected as the classification features, and the accuracy rate of recognition could reach more than 70 percent.

Details

Database :
OpenAIRE
Journal :
2019 6th International Conference on Information Science and Control Engineering (ICISCE)
Accession number :
edsair.doi...........5e3ed631f820c90be1aa3ffe088b6621
Full Text :
https://doi.org/10.1109/icisce48695.2019.00059