EEG-based lie detection using ERP P300 in response to known and unknown faces: An overview

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F22%3A63557458" target="_blank" >RIV/70883521:28140/22:63557458 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10017818" target="_blank" >https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10017818</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CSCC55931.2022.00011" target="_blank" >10.1109/CSCC55931.2022.00011</a>

Jazyk výsledku

angličtina

Název v původním jazyce

EEG-based lie detection using ERP P300 in response to known and unknown faces: An overview

Popis výsledku v původním jazyce

Concealed information detection is nowadays an essential part of security. Conventional lie detectors are expensive, time-consuming, and their accuracy depends on the subject. Many researchers have focused on investigating concealed information for lie detection using electroencephalography (EEG) to recognize a lie better. This work aimed to provide an overview of scientific studies on EEGbased lie detection in the context of ERP P300 during the presentation of known and unknown faces published in the last five years (2017-2022). To the best of our knowledge, there is no recent available review of the most used methods for EEG data analysis in this field. For that reason, this article was created containing the current most used methods for feature extraction and classification, protocols, and accuracy of individual approaches.

Název v anglickém jazyce

EEG-based lie detection using ERP P300 in response to known and unknown faces: An overview

Popis výsledku anglicky

Concealed information detection is nowadays an essential part of security. Conventional lie detectors are expensive, time-consuming, and their accuracy depends on the subject. Many researchers have focused on investigating concealed information for lie detection using electroencephalography (EEG) to recognize a lie better. This work aimed to provide an overview of scientific studies on EEGbased lie detection in the context of ERP P300 during the presentation of known and unknown faces published in the last five years (2017-2022). To the best of our knowledge, there is no recent available review of the most used methods for EEG data analysis in this field. For that reason, this article was created containing the current most used methods for feature extraction and classification, protocols, and accuracy of individual approaches.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2022 26th International Conference on Circuits, Systems, Communications and Computers (CSCC)

ISBN

978-1-66548-186-1

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

11-15

Název nakladatele

IEEE Computer Society Conference Publishing Services (CPS)

Místo vydání

Washington, DC

Místo konání akce

Chania

Datum konání akce

19. 7. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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