Ing. Martina Žabčíková

DETECTION OF CONCEALED INFORMATION USING ELECTROENCEPHALOGRAPHY

Analyzing deceptive behaviour in humans is one of the main challenges where legal and security purposes are considered. Currently, the polygraph is the most widely used device for lie detection. However, its accuracy and reliability vary in investigative problems as the subject can control his physiological responses. Brain signals are used to detect concealed information in the brain to lie detection to overcome this problem. EEG-based lie detectors have become popular over polygraphs because they cannot be controlled by human intentions. The goal of the work is to identify the most commonly used procedures, methods, and algorithms in recent research for lie detection using EEG. For this purpose, a literature review was compiled from various databases. It was found that the most used method for analyzing an individual's lying behaviour is the Concealed Information Test (CIT) based on the ERP P300 paradigm. Further, this work will present an experimental proposal for detecting concealed information for lie identification using CIT based on the ERP P300 paradigm.