A Real-Time Approach to Classify EEG Signals for Identifying Prevarication

被引：0

作者：

Kesavan, Nandhini ^{[1
]}

Raajan, Narasimhan Renga ^{[1
]}

机构：

[1] SASTRA Univ, Thanjavur, India

来源：

NATIONAL ACADEMY SCIENCE LETTERS-INDIA | 2019年 / 42卷 / 01期

关键词：

EEG; MLP; Bagging; P300; Classification; CLASSIFICATION; SELECTION;

D O I：

10.1007/s40009-018-0737-8

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Electroencephalography (EEG) is a recording method which captures brain action. In these frameworks, clients unequivocally control their brain action as opposed to utilizing motor movements to create signals that can be utilized to control computers or specialized gadgets. In this research, classifiers such as multilayer perceptron and bagging are utilized to quantify the exactness and accuracy of the acquired mind information. The percentage of recognition plays a major role as it indicates the person, the ratio he is in synch with viewing and thinking. EEG signal and P300 are used to measure the recordings done in the brain. On comparing the results of EEG and P300, it was found that recognition rate was good with the latter.

引用

页码：33 / 37

页数：5

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