[1]杨建平,刘明华,吕敬祥,等.低觉醒脑电识别与唤醒的可穿戴系统研究[J].智能系统学报,2019,14(04):787-792.[doi:10.11992/tis.201806047]
 YANG Jianping,LIU Minghua,LYU Jingxiang,et al.A wearable system to recognize and awaken low-arousal state[J].CAAI Transactions on Intelligent Systems,2019,14(04):787-792.[doi:10.11992/tis.201806047]
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低觉醒脑电识别与唤醒的可穿戴系统研究(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第14卷
期数:
2019年04期
页码:
787-792
栏目:
出版日期:
2019-07-02

文章信息/Info

Title:
A wearable system to recognize and awaken low-arousal state
作者:
杨建平 刘明华 吕敬祥 孔翠香 帅晓勇
井冈山大学 电子与信息工程学院, 江西 吉安 343009
Author(s):
YANG Jianping LIU Minghua LYU Jingxiang KONG Cuixiang SHUAI Xiaoyong
School of Electronics and Information Engineering, Jinggangshan University, Ji’an 343009, China
关键词:
现场可编程门阵列脑电信号低觉醒状态警戒作业支持向量机相对能量重心频率谱熵
Keywords:
field-programmable gate array (FPGA)electroencephalogramlow arousal statevigilance operationsupport vector machinerelative energygravity frequencyspectrum entropy
分类号:
TP391
DOI:
10.11992/tis.201806047
摘要:
为智能化地识别警戒作业人员出现的低觉醒、注意力下降的生理状态,本文介绍了一种基于FPGA和脑电信号处理的低觉醒状态检测与唤醒系统,系统通过传感器从大脑头皮采集脑电信号,转换为数字信号,经傅里叶变换获取了脑电信号的θ相对能量、α相对能量、重心频率、谱熵等4个特征量,由4个特征量表征低觉醒状态并运用支持向量机对低警戒状态进行识别,当识别出低觉醒状态时采用声音报警模块发出声音,唤醒警戒作业人员。设计系统能够较好地识别出低觉醒状态,识别率达90.8%,可为提高警戒作业工作绩效提供一种可穿戴的智能装备。
Abstract:
To intelligently identify the physiological state of vigilance workers with low awakening and low attention, this paper presents a monitoring and awakening system for low arousal/vigilance state based on the field-programmable gate array (FPGA) and electroencephalogram (EEG) signals processing. The system collects EEG signals from the scalp, converts the analog signals to digital signals, and then uses Fourier transform to calculate its power spectrum. The system subsequently acquires four eigenvectors-the relative energies of the θ and α, the gravity frequency, and the spectrum entropy-which are used to characterize the low arousal state, and on this basis, the support vector machine (SVM) is used to recognize the low arousal state. Once the low arousal state is identified, the SVM will awaken the vigilance worker using a sound alarm module. The system can effectively distinguish the low awakening state, and the recognition rate reaches 90.8%. Moreover, it can provide a wearable intelligent equipment to improve performance of vigilance operations.

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备注/Memo

备注/Memo:
收稿日期:2018-06-30。
基金项目:国家自然科学基金项目(11761038);江西省教育厅科技项目(GJJ13542).
作者简介:杨建平,男,1970年生,副教授,主要研究方向为人工神经网络、模式识别、智能信息处理。发表学术论文20余篇;刘明华,男,1975年生,副教授,博士,主要研究方向为非线性电路与系统、智能信息处理。发表学术论文近20篇;吕敬祥,男,1977年生,讲师,博士,主要研究方向为无线传感网路由协议及数据融合。发表学术论文20余篇。
通讯作者:杨建平.E-mail:yangjp9273@163.com
更新日期/Last Update: 2019-08-25