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Threat Perception Captured by Emotion, Motor and Empathetic System Responses: A Systematic Review.

Authors :
Jacobs, Elizabeth Michelle
Deligianni, Fani
Pollick, Frank
Source :
IEEE Transactions on Affective Computing; Jul-Sep2024, Vol. 15 Issue 3, p1116-1135, 20p
Publication Year :
2024

Abstract

The fight or flight phenomena is of evolutionary origin and responsible for the type of defensive behaviours enacted, when in the face of threat. This review attempts to draw the link between fear and aggression as motivational levers for fight or flight defensive behaviours. Furthermore, this review investigates whether human biological motion is modulated by the affective behaviours associated with the fight or flight phenomenon. It examines how threat informed emotion and motor systems have the potential to result in the modulation of empathetic appraisal. This is of interest to this systematic review, as empathetic modulation is crucial to prosocial drive, which has the potential to alleviate the perceived threat. Hence, this review investigates the role of affective computing in capturing the potential outcome of threat perception and associated empathetic responses. To gain a comprehensive understanding of the affective responses and biological motion evoked from threat scenarios, affective computing methods used to capture these neurophysiological and behavioural responses are discussed. A systematic review using Google Scholar and Web of Science was conducted as of 2023, and findings were supplemented by bibliographies of key articles. A total of 26 studies were analysed from initial web searches to explore the topics of empathy, threat perception, fight or flight, fear, aggression, and human motion. Relationships between affective behaviours (fear, aggression) and corresponding motor defensive behaviours (fight or flight) were examined within threat scenarios, and whether existing affective computing methods are effective in capturing these responses, identifying the varying consensus in the literature, challenges, and limitations of existing research. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19493045
Volume :
15
Issue :
3
Database :
Complementary Index
Journal :
IEEE Transactions on Affective Computing
Publication Type :
Academic Journal
Accession number :
179509519
Full Text :
https://doi.org/10.1109/TAFFC.2023.3323043