Our own action kinematics predict the perceived affective states of others
Edey, Rosanna and Yon, Daniel and Cook, J. and Dumontheil, Iroise and Press, Clare (2017) Our own action kinematics predict the perceived affective states of others. Journal of Experimental Psychology: Human Perception and Performance 43 (7), pp. 1263-1268. ISSN 0096-1523.
|
Text
EmPer MS+Supp Final.pdf - Author's Accepted Manuscript Download (620kB) | Preview |
Abstract
Our movement kinematics provide useful cues about our affective states. Given that our experiences furnish models that help us to interpret our environment, and that a rich source of action experience comes from our own movements, the present study examined whether we use models of our own action kinematics to make judgments about the affective states of others. For example, relative to one’s typical kinematics, anger is associated with fast movements. Therefore, the extent to which we perceive anger in others may be determined by the degree to which their movements are faster than our own typical movements. We related participants’ walking kinematics in a neutral context to their judgments of the affective states conveyed by observed point-light walkers (PLWs). As predicted, we found a linear relationship between one’s own walking kinematics and affective state judgments, such that faster participants rated slower emotions more intensely relative to their ratings for faster emotions. This relationship was absent when observing PLWs where differences in velocity between affective states were removed. These findings suggest that perception of affective states in others is predicted by one’s own movement kinematics, with important implications for perception of, and interaction with, those who move differently.
Metadata
Item Type: | Article |
---|---|
Additional Information: | This article may not exactly replicate the final version published in the APA journal. It is not the copy of record. |
School: | Birkbeck Faculties and Schools > Faculty of Science > School of Psychological Sciences |
Depositing User: | Clare Press |
Date Deposited: | 01 Mar 2017 16:28 |
Last Modified: | 02 Aug 2023 17:31 |
URI: | https://eprints.bbk.ac.uk/id/eprint/18243 |
Statistics
Additional statistics are available via IRStats2.