Experimental approach to the recognition of truthful and false mental responses based on the wavelet transform of the electroencephalogram

Yumatov Ea, Potapov Vyu, Karatygin Na, Dudnik En, Pertsov Ss
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引用次数: 1

Abstract

An existing polygraph technique to evaluate the faithfulness of the verbal response is based on recoding of psychophysiological and somatic-and-autonomic indices, which do not reflect the actual deceitful or truthful state of the subject's brain. The advanced method of electroencephalogram wavelet transform was developed in recent years. This approach allowed us to determine a principle possibility for the direct, objective recording of mental activity in the human brain. The overall goal of the research is to develop a fundamentally new information technology to identify a truthful and deceitful state in the brain mental activity, which suggests the wavelet transform of the electroencephalogram and machine learning. For this purpose, an experimental model and software have been created and described in the article for recognizing the truthful and false mental responses of a person based on the electroencephalogram analysis. The software was developed with Microsoft Visual Studio 2017 and Net Framework 4.5. This software is simple in use and works with the Russian language interface. The developed experimental model and information-software allow us to compare electroencephalographic indicators of two mental states of brain activity, one of which is deceitful, and the other is truthful. *Correspondence to: Yumatov EA, PK Anokhin Research Institute of Normal Physiology, Moscow, Russia, E-mail: eayumatov@mail.ru
基于脑电图小波变换的真假心理反应识别实验方法
现有的一种测谎技术是基于对心理生理和身体自主指数的重新编码来评估口头反应的真实性,而这些指数并不能反映受试者大脑的真实或欺骗状态。脑电图小波变换是近年来发展起来的一种先进的方法。这种方法使我们确定了直接、客观地记录人脑心理活动的基本可能性。该研究的总体目标是开发一种全新的信息技术,以识别大脑心理活动中的真实和欺骗状态,这暗示了脑电图的小波变换和机器学习。为此,本文创建并描述了一个实验模型和软件,用于根据脑电图分析识别人的真实和虚假心理反应。该软件是使用Microsoft Visual Studio 2017和。Net Framework 4.5开发的。该软件使用简单,并与俄语界面工作。开发的实验模型和信息软件使我们能够比较大脑活动的两种精神状态的脑电图指标,其中一种是欺骗性的,另一种是真实的。*通信:Yumatov EA, PK Anokhin正常生理研究所,莫斯科,俄罗斯,E-mail: eayumatov@mail.ru
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