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.
Highlights
Nonverbal cues to deception have been studied for decades, the current literature is characterized by inconsistent and often contradictory findings, leading many researchers to focus their research on verbal cues [1]
We started this paper by noting that research on nonverbal indicators of deceit has reported inconsistent and even contradictory results [9] and that the identified cues often have a weak relationship with veracity [6, 7, 8, 9]
With a medium effect size of .26 (Pearson’s r), our results indicate that full body motion is a reliable nonverbal indicator of deceit
Summary
Nonverbal cues to deception have been studied for decades, the current literature is characterized by inconsistent and often contradictory findings, leading many researchers to focus their research on verbal cues [1]. Meservy et al [29] were able to correctly identify deceit with 71% accuracy using a neural network with input from facial expressions and gestures; and analyses of hand and face movement have been used to automatically classify deception-related behaviors such as agitation and behavioral control [33] These studies provide an objective measure of specific types of deceptive behavior, they are often limited to examining facial expressions [31, 32] or specific body parts such as the face and hands [29, 33]. Because theoretical models (i.e., the emotional, cognitive load, and attempted behavioral control approaches) [6] and empirical research have demonstrated that movement can both increase and decrease when lying [2, 3, 4, 5], we refrained from postulating directive hypotheses
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