基于单通道脑电信号的疲劳检测系统

doi:10.11896/jsjkx.190400127

计算机科学 ›› 2020, Vol. 47 ›› Issue (5): 225-229.doi: 10.11896/jsjkx.190400127

基于单通道脑电信号的疲劳检测系统

王博石, 吴修诚, 胡馨艺, 张莉

重庆大学电气工程学院重庆400044

收稿日期:2019-04-23 出版日期:2020-05-15 发布日期:2020-05-19
通讯作者: 吴修诚(1215942547@qq.com)
作者简介:493733680@qq.com

Fatigue Detection System Based on Single Channel EEG Signal

WANG Bo-shi, WU Xiu-cheng, HU Xin-yi, ZHANG Li

School of Electrical Engineering,Chongqing University,Chongqing 400044,China

Received:2019-04-23 Online:2020-05-15 Published:2020-05-19
About author:WANG Bo-shi,born in 1997,postgra-duate.His main research interests include brain-computer interface and so on.
WU Xiu-cheng,born in 1998,postgra-duate.His main research interests include electrical engineering and automation.

摘要/Abstract

摘要： 针对目前高强度劳动人群频繁猝死的情况,文中设计了一套基于单通道脑电信号(Electroencephalography,EEG)的疲劳检测系统,以实现对该类人群疲劳程度的准确判定,起到预警效果。系统利用TGAM(ThinkGearm AM)脑电模块采集原始EEG数据,通过蓝牙方式将数据传送至上位机,在上位机中提取EEG的4个基本节律成分(δ,θ,α,β),以节律信号的相对频带能量作为表征疲劳状态的脑电特征,并利用Fisher判别分析(Fisher Discriminant Analysis,FDA)和概率神经网络(Probabilistic Neural Network,PNN)两种方法对脑电特征进行分类,给出评估结果。实验结果表明,所设计的基于单通道EEG的疲劳检测系统能够实现准确率较高的疲劳状态检测。

关键词: EEG, FDA算法, GUI, TGAM脑电模块, 基本节律

Abstract: For sudden death in people with high labor intensity,this paper designs a fatigue detection system based on single-channel EEG to realize accurate judgment of the fatigue level in order to make a timely warning for this kind of people.The system uses the TGAM(ThinkGear AM) to collect the original EEG data,transmits the data to the host computer via Bluetooth,and extracts four basic rhythm components (δ,θ,α,β) of the EEG in the host computer.The relative frequency band energies of some rhythms are used as the EEG features characterizing fatigue state,and Fisher discriminant analysis(FDA) and probabilistic neural network(PNN) are used to classify EEG features.Finally,the evaluation results are given.The experimental results show that the designed single-channel EEG-based fatigue detection system can achieve high accuracy of fatigue state detection.

Key words: Basic rhythm, EEG, FDA algorithm, GUI, TGAM EEG module

中图分类号:

TP391.4

王博石, 吴修诚, 胡馨艺, 张莉. 基于单通道脑电信号的疲劳检测系统[J]. 计算机科学, 2020, 47(5): 225-229. https://doi.org/10.11896/jsjkx.190400127

WANG Bo-shi, WU Xiu-cheng, HU Xin-yi, ZHANG Li. Fatigue Detection System Based on Single Channel EEG Signal[J]. Computer Science, 2020, 47(5): 225-229. https://doi.org/10.11896/jsjkx.190400127

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基于单通道脑电信号的疲劳检测系统

Fatigue Detection System Based on Single Channel EEG Signal

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