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To freeze or not to freeze: A culture-sensitive motion capture approach to detecting deceit

Published version
Peer-reviewed

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Type

Article

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Authors

Anderson, RJ 
van der Zee, Sophie 
Poppe, Ronald 
Taylor, Paul J 

Abstract

We present a new signal for detecting deception: full body motion. Previous work on detecting deception from body movement has relied either on human judges or on specific gestures (such as fidgeting or gaze aversion) that are coded by humans. While this research has helped to build the foundation of the field, results are often characterized by inconsistent and contradictory findings, with small-stakes lies under lab conditions detected at rates little better than guessing. We examine whether a full body motion capture suit, which records the position, velocity, and orientation of 23 points in the subject’s body, could yield a better signal of deception. Interviewees of South Asian (n = 60) or White British culture (n = 30) were required to either tell the truth or lie about two experienced tasks while being interviewed by somebody from their own (n = 60) or different culture (n = 30). We discovered that full body motion–the sum of joint displacements–was indicative of lying 74.4% of the time. Further analyses indicated that including individual limb data in our full body motion measurements can increase its discriminatory power to 82.2%. Furthermore, movement was guilt- and penitential-related, and occurred independently of anxiety, cognitive load, and cultural background. It appears that full body motion can be an objective nonverbal indicator of deceit, showing that lying does not cause people to freeze.

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Keywords

Adolescent, Adult, Aged, Aged, 80 and over, Asian People, Culture, Deception, Female, Humans, Male, Middle Aged, Nonverbal Communication, White People

Journal Title

PLoS ONE

Conference Name

Journal ISSN

1932-6203
1932-6203

Volume Title

14

Publisher

Public Library of Science (PLoS)
Sponsorship
Engineering and Physical Sciences Research Council (EP/K033476/1)
The research presented in this paper was part funded by the Centre for Research and Evidence on Security Threats, website: https://crestresearch.ac.uk/. Funding source: Economic and Social Research Council (ESRC) Award: ES/N009614/1 and EPSRC grant EP/K033476/1 by Ross Anderson.