Jacobs, E.M., Deligianni, F. and Pollick, F. (2023) Threat perception captured by emotion, motor and empathetic system responses: a systematic review. IEEE Transactions on Affective Computing, (doi: 10.1109/TAFFC.2023.3323043) (Early Online Publication)
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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 behavioural motivations for fight or flight defensive behaviours. Hence, this review intends to examine whether fight or flight behavioural responses are the result of fear and aggression. Furthermore, this review investigates whether human biological motion captures the affective states associated with the fight or flight phenomenon. This review also aims to investigate how threat informed emotion and motor systems have the potential to result in empathetic appraisal modulation. This is of interest to this systematic review, as empathetic modulation is crucial to prosocial drive, which has the potential to increase the inclination of alleviating the perceived threat of another. Hence, this review investigates the role of affective computing in capturing the potential outcome of empathy from threat perception. To gain a comprehensive understanding of the affective states and biological motion evoked from threat scenarios, affective computing methods used to capture these 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 22 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 states (fear, aggression) and corresponding motor defensive behaviours (fight or flight) were examined within threat scenarios, and whether existing affective computing methods are succinct in capturing these responses, identifying the varying consensus in the literature, challenges, and limitations of existing research.
| Item Type: | Articles |
|---|---|
| Additional Information: | This work was supported by the UKRI centre for Doctoral Training in Socially Intelligent Artificial Agents, Grant Number EPS02266X1, the Engineering and Physical Sciences Research Council, Grant Number EPW01212X1 and Royal Society, Grant Number RGSR2212199. |
| Status: | Early Online Publication |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Deligianni, Dr Fani and Pollick, Professor Frank and Jacobs, Elizabeth |
| Authors: | Jacobs, E.M., Deligianni, F., and Pollick, F. |
| College/School: | College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience College of Science and Engineering > School of Computing Science |
| Journal Name: | IEEE Transactions on Affective Computing |
| Publisher: | IEEE |
| ISSN: | 1949-3045 |
| ISSN (Online): | 1949-3045 |
| Published Online: | 09 October 2023 |
| Copyright Holders: | Copyright © 2024 IEEE |
| First Published: | First published in IEEE Transactions on Affective Computing 2024 |
| Publisher Policy: | Reproduced with the permission of the publisher |
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