Determining the state of truthfulness and falsehood by analyzing the acquired EEG signals

Detection of deception is particular importance for the criminal case and cognitive behaviors of individual. To understanding criminal behavior, extracting the characteristic of brain waves have obviously crucial. According to hypothesis, particularly prefrontal lobes associated with the deception....

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Main Authors:	Cakmak, Rumeysa, Zeki, Akram M.
Format:	Conference or Workshop Item
Language:	English English
Published:	Institute of Electrical and Electronics Engineers Inc. 2016
Subjects:	TK5101 Telecommunication. Including telegraphy, radio, radar, television
Online Access:	http://irep.iium.edu.my/58531/ http://irep.iium.edu.my/58531/ http://irep.iium.edu.my/58531/ http://irep.iium.edu.my/58531/1/58531_Determining%20the%20state%20of%20truthfulness_SCOPUS.pdf http://irep.iium.edu.my/58531/2/58531_Determining%20the%20state%20of%20truthfulness.pdf

id	iium-58531
recordtype	eprints
spelling	iium-585312017-10-12T09:07:36Z http://irep.iium.edu.my/58531/ Determining the state of truthfulness and falsehood by analyzing the acquired EEG signals Cakmak, Rumeysa Zeki, Akram M. TK5101 Telecommunication. Including telegraphy, radio, radar, television Detection of deception is particular importance for the criminal case and cognitive behaviors of individual. To understanding criminal behavior, extracting the characteristic of brain waves have obviously crucial. According to hypothesis, particularly prefrontal lobes associated with the deception. This paper alleged to understanding the relationship between deception and truth from frontal lobe during some specific tasks by mapping their EEG signals. In the present study, multiplayer neural network are used for bio-signal classification to diversify between patterns of lie and truth types of EEG classes with the accuracy of around 96%. Brain activity have been captured and characterized with EEG by focusing alpha waves. During the test, lie detection identified and especially focus to detect lie in individual subjects, rather than group averages. In this research, the classification methods applied and EEG machine differentiated the specific patterns of brain activity from frontal lobes associated with deception and truth. The responses from the 3 subjects was discriminated correctly with 99%. The ranges of accuracy of test from three subjects was between 88% to 96%, there was an exception in round three with subject three with 46%. While the participants were playing with Pokemon card, alpha waves were collected successfully. © 2016 IEEE. Institute of Electrical and Electronics Engineers Inc. 2016-07-18 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/58531/1/58531_Determining%20the%20state%20of%20truthfulness_SCOPUS.pdf application/pdf en http://irep.iium.edu.my/58531/2/58531_Determining%20the%20state%20of%20truthfulness.pdf Cakmak, Rumeysa and Zeki, Akram M. (2016) Determining the state of truthfulness and falsehood by analyzing the acquired EEG signals. In: 12th IEEE International Colloquium on Signal Processing and its Applications, CSPA 2016, 4th-6th March 2016, Hatten Hotel MelakaHatten Square, Bandar HilirMelaka. http://ieeexplore.ieee.org/document/7515826/ 10.1109/CSPA.2016.7515826
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TK5101 Telecommunication. Including telegraphy, radio, radar, television
spellingShingle	TK5101 Telecommunication. Including telegraphy, radio, radar, television Cakmak, Rumeysa Zeki, Akram M. Determining the state of truthfulness and falsehood by analyzing the acquired EEG signals
description	Detection of deception is particular importance for the criminal case and cognitive behaviors of individual. To understanding criminal behavior, extracting the characteristic of brain waves have obviously crucial. According to hypothesis, particularly prefrontal lobes associated with the deception. This paper alleged to understanding the relationship between deception and truth from frontal lobe during some specific tasks by mapping their EEG signals. In the present study, multiplayer neural network are used for bio-signal classification to diversify between patterns of lie and truth types of EEG classes with the accuracy of around 96%. Brain activity have been captured and characterized with EEG by focusing alpha waves. During the test, lie detection identified and especially focus to detect lie in individual subjects, rather than group averages. In this research, the classification methods applied and EEG machine differentiated the specific patterns of brain activity from frontal lobes associated with deception and truth. The responses from the 3 subjects was discriminated correctly with 99%. The ranges of accuracy of test from three subjects was between 88% to 96%, there was an exception in round three with subject three with 46%. While the participants were playing with Pokemon card, alpha waves were collected successfully. © 2016 IEEE.
format	Conference or Workshop Item
author	Cakmak, Rumeysa Zeki, Akram M.
author_facet	Cakmak, Rumeysa Zeki, Akram M.
author_sort	Cakmak, Rumeysa
title	Determining the state of truthfulness and falsehood by analyzing the acquired EEG signals
title_short	Determining the state of truthfulness and falsehood by analyzing the acquired EEG signals
title_full	Determining the state of truthfulness and falsehood by analyzing the acquired EEG signals
title_fullStr	Determining the state of truthfulness and falsehood by analyzing the acquired EEG signals
title_full_unstemmed	Determining the state of truthfulness and falsehood by analyzing the acquired EEG signals
title_sort	determining the state of truthfulness and falsehood by analyzing the acquired eeg signals
publisher	Institute of Electrical and Electronics Engineers Inc.
publishDate	2016
url	http://irep.iium.edu.my/58531/ http://irep.iium.edu.my/58531/ http://irep.iium.edu.my/58531/ http://irep.iium.edu.my/58531/1/58531_Determining%20the%20state%20of%20truthfulness_SCOPUS.pdf http://irep.iium.edu.my/58531/2/58531_Determining%20the%20state%20of%20truthfulness.pdf
first_indexed	2023-09-18T21:22:46Z
last_indexed	2023-09-18T21:22:46Z
_version_	1777411992417468416

Determining the state of truthfulness and falsehood by analyzing the acquired EEG signals

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