4.7 Article

Functional brain network and multichannel analysis for the P300-based brain computer interface system of lying detection

期刊

EXPERT SYSTEMS WITH APPLICATIONS
卷 53, 期 -, 页码 117-128

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2016.01.024

关键词

Lie detection; Event related potential; Brain computer interface; Bootstrapped geometric difference; Nonlinear interdependence; Graph theory

资金

  1. National Natural Science Foundation of China [51405073]
  2. University Innovation Team of Liaoning Province [LT2014006]
  3. Key Laboratory of Impression Evidence Examination and Identification Technology
  4. Ministry of Public Security, People's Republic of China [SY110035]

向作者/读者索取更多资源

Deception is a complex cognition process which involves activities in different brain regions. However, most of the ERP based lie detection systems focus on the features of ERPs from few channels. In this study, we designed a multi-channel ERP based brain computer interface (BCI) system for lie detection. Based on this, two new EEG feature selection approaches, bootstrapped geometric difference (BGD) and network analysis were proposed and applied to feature recognition and classification system. Unlike other methods, our approaches focus on the changes of EEGs from different brain regions and the correlation between them. For the test, we focus on visual and auditory stimuli, two groups of subjects went through the test and their EEGs were recorded. For all subjects, BGD of the P300 for all the scalp electrodes combined with SVM classifier showed the average rate of recognition accuracy was 84.4% and 82.2% for visual and auditory modality respectively. Statistical analysis of network features indicated the difference in the two groups were significant and the average accuracy rate reached 88.7% and 83.5% respectively, and the guilty group showed more obvious small-world property than innocent group. The results suggest the BGD and network analysis based approaches combined with SVM are efficient for ERP based expert and intelligent system for detection and evaluation of deception. The combination of these methods and other feature selection approaches can promote the development and application of ERP based lie detection system.(C) 2016 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据