基于听觉ERP功能脑网络特征和SVM的测谎方法研究

doi:10.3969/j.issn.0372-2112.2016.07.034

电子学报 ›› 2016, Vol. 44 ›› Issue (7): 1757-1762.DOI: 10.3969/j.issn.0372-2112.2016.07.034

基于听觉ERP功能脑网络特征和SVM的测谎方法研究

常文文, 王宏, 化成诚

东北大学机械工程与自动化学院, 辽宁沈阳 110819

收稿日期:2015-07-06 修回日期:2015-08-05 出版日期:2016-07-25
- 通讯作者:
- 王宏
- 作者简介:
- 常文文 男,1987年生,甘肃通渭人,东北大学博士研究生,主要研究方向为事件相关脑电,脑机-接口,脑电信号处理.E-mail:changww2013@126.com
- 基金资助:
- 国家自然科学基金 (No.51405073); 辽宁省创新团队基金 (No.LT2014006)

Study on Lie Detection Method Based on Auditory ERP Functional Brain Network Characteristic and SVM

CHANG Wen-wen, WANG Hong, HUA Cheng-cheng

School of Mechanical Engineering & Automation, Northeastern University, Shenyang, Liaoning 110819, China

Received:2015-07-06 Revised:2015-08-05 Online:2016-07-25 Published:2016-07-25

摘要/Abstract

摘要：

基于图论理论的脑网络分析方法近年来在认知脑科学研究中起到了非常重要的作用,而基于事件相关电位(Event-Related Potentials,ERP)的传统测谎方法一直都专注于对某一特定通道上的脑电信号进行分析,针对传统方法中使用少数通道并不能够全面的反映人在说谎状态下大脑整体认知功能特征的缺点,本文提出了基于脑网络特征的测谎方法,通过听觉刺激诱发事件相关电位ERP,记录脑区多通道脑电信号,通过讨论各导联之间的相位延迟指数来构建脑功能网络,计算7类脑网络特征参数作为判别指标.分析被试在说谎和无辜状态下的网络特征参数,使用支持向量机对实验数据进行分类判断,结果表明:本文提出的方法有较高的判别准确率,优于目前判别方法的平均值,证明了本方法的测谎有效性.

关键词: 脑电, 测谎, 听觉刺激, 小波包, 相位延迟指数, 脑功能网络

Abstract:

Recently,brain network method,which based on grapy theory,has played an important role in cognitive science research.And the traditional lie detection methods,which based on ERP signals,usually focus on the EEG from one channel,this has some shortcomings,that use few channels are not able to reflect the whole cognitive characteristic underlying lie condition.In this paper,we proposed a method based on brain network characteristics.We used the auditory stimuli to evoke the ERP signals and it was recorded from different channels.In order to build the functional brain network,we calculated the phase lag index between these channels,and seven network parameters were calculated as the index for lie detection.Those network parameters were compared between guilty and innocent subjects,and support vector machine was used as the classifier to the test date.The result shows that this method has a higher identify accuracy than the average accuracy of existing method,proved the validity of the method.

Key words: Electroencephalogram (EEG), lie detection, auditory stimuli, wavelet packet, phase lag index, brain network

中图分类号:

R318

常文文, 王宏, 化成诚. 基于听觉ERP功能脑网络特征和SVM的测谎方法研究[J]. 电子学报, 2016, 44(7): 1757-1762.

CHANG Wen-wen, WANG Hong, HUA Cheng-cheng. Study on Lie Detection Method Based on Auditory ERP Functional Brain Network Characteristic and SVM[J]. Acta Electronica Sinica, 2016, 44(7): 1757-1762.

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基于听觉ERP功能脑网络特征和SVM的测谎方法研究

Study on Lie Detection Method Based on Auditory ERP Functional Brain Network Characteristic and SVM

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