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Title
Leye (Lie) Detector \u2014 A Study of Lie Detection using Eye Tracking, Facial Gestures, and EEG
Description
Lie detection is used prominently in contemporary society for many purposes such as for pre-employment screenings, granting security clearances, and determining if criminals or potential subjects may or may not be lying, but by no means is not limited to that scope. However, lie detection has been criticized for being subjective, unreliable, inaccurate, and susceptible to deliberate manipulation. Furthermore, critics also believe that the administrator of the test also influences the outcome as well. As a result, the polygraph machine, the contemporary device used for lie detection, has come under scrutiny when used as evidence in the courts. The purpose of this study is to use three entirely different tools and concepts to determine whether eye tracking systems, electroencephalogram (EEG), and Facial Expression Emotion Analysis (FACET) are reliable tools for lie detection. This study found that certain constructs such as where the left eye is looking at in regard to its usual position and engagement levels in eye tracking and EEG respectively could distinguish between truths and lies. However, the FACET proved the most reliable tool out of the three by providing not just one distinguishing variable but seven, all related to emotions derived from movements in the facial muscles during the present study. The emotions associated with the FACET that were documented to possess the ability to distinguish between truthful and lying responses were joy, anger, fear, confusion, and frustration. In addition, an overall measure of the subject's neutral and positive emotional expression were found to be distinctive factors. The implications of this study and future directions are discussed.
Date Created
2017-05
Contributors
- Seto, Raymond Hua (Author)
- Atkinson, Robert (Thesis director)
- Runger, George (Committee member)
- W. P. Carey School of Business (Contributor)
- Computer Science and Engineering Program (Contributor)
- Barrett, The Honors College (Contributor)
Topical Subject
Resource Type
Extent
46 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Series
Academic Year 2016-2017
Handle
https://hdl.handle.net/2286/R.I.43723
Level of coding
minimal
Cataloging Standards
System Created
- 2017-10-30 02:50:58
System Modified
- 2021-08-11 04:09:57
- 3 years 2 months ago
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