Event Related Potential (ERP) based Lie Detection using a Wearable EEG headset

S. Anwar, Tahira Batool, Muhammad Majid
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引用次数: 8

Abstract

Polygraph based detection systems have been used for performing guilty knowledge test (GKT) over a long period of time. More recently the advances in medical imaging techniques have resulted in a better understanding of brain activity. These techniques (e.g. functional magnetic resonance imaging) have allowed researchers to generate applications that are based on the enhanced understanding of brain function. Detection of concealed information using brain activity is explored in this study as a better alternative to a Polygraph. Electroencephalography (EEG) allows decoding brain signals with a higher temporal resolution by applying smart signal processing techniques. In this work a commercial off the shelf wearable EEG headset is used to record brain signals in an information concealment testing environment. Although the use of such setup restricts the number of EEG channels available to the detection algorithm, but it provides portability and ease of use when compared to clinical EEG setup. The proposed algorithm is designed to give optimum results in terms of accuracy and computation time with emphasis on an easily deployable system.
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基于事件相关电位(ERP)的可穿戴式脑电图头戴式测谎仪
长期以来,基于测谎仪的检测系统一直被用于进行有罪认知测试(GKT)。最近,医学成像技术的进步使人们对大脑活动有了更好的了解。这些技术(如功能性磁共振成像)使研究人员能够基于对大脑功能的增强理解而产生应用。在这项研究中,利用大脑活动来检测隐藏信息是一种比测谎仪更好的选择。脑电图(EEG)通过应用智能信号处理技术,可以以更高的时间分辨率解码大脑信号。在本研究中,我们使用了一种商用的现成的可穿戴式脑电图耳机,在信息隐藏测试环境中记录大脑信号。虽然使用这种设置限制了检测算法可用的EEG通道数量,但与临床EEG设置相比,它提供了可移植性和易用性。所提出的算法在精度和计算时间方面给出了最佳结果,重点是一个易于部署的系统。
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