Contact Us | Language: čeština English
Title: | Concealed information detection using EEG for lie recognition by ERP P300 in response to visual stimuli: A review | ||||||||||
Author: | Žabčíková, Martina; Koudelková, Zuzana; Jašek, Roman | ||||||||||
Document type: | Peer-reviewed article (English) | ||||||||||
Source document: | WSEAS Transactions on Information Science and Applications. 2022, vol. 19, p. 171-179 | ||||||||||
ISSN: | 1790-0832 (Sherpa/RoMEO, JCR) | ||||||||||
Journal Impact
This chart shows the development of journal-level impact metrics in time
|
|||||||||||
DOI: | https://doi.org/10.37394/23209.2022.19.17 | ||||||||||
Abstract: | Nowadays, lie detection based on electroencephalography (EEG) is a popular area of research. Current lie detectors can be controlled voluntarily and have several disadvantages. EEG-based lie detectors have become popular over polygraphs because human intentions cannot control them, are not based on subjective interpretation, and can therefore detect lies better. This paper's main objective was to give an overview of the scientific works on the recognition of concealed information using EEG for lie detection in response to visual stimuli of faces, as there is no existing review in this area. These were selected publications from the Web of Science (WoS) database published over the last five years. It was found that the Event-Related Potential (ERP) P300 is the most often used method for this purpose. The article contains a detailed overview of the methods used in scientific research in EEG-based lie detection using the ERP P300 component in response to known and unknown faces. © 2022 World Scientific and Engineering Academy and Society. All right reserved. | ||||||||||
Full text: | https://wseas.com/journals/articles.php?id=7201 | ||||||||||
Show full item record |