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

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.