Individual and joint body movement assessed by wearable sensing as a predictor of attraction in speed dates

Individual and joint body movement assessed by wearable sensing as a predictor of attraction in speed dates

Vargas Quiros, J.D. (TU Delft Pattern Recognition and Bioinformatics)
Kapcak, Oyku (Student TU Delft)
Hung, H.S. (TU Delft Pattern Recognition and Bioinformatics)
Cabrera Quiros, L.C. (Costa Rican Institute of Technology)

2023

Interpersonal attraction is known to motivate behavioral responses in the person experiencing this subjective phenomenon. Such responses may involve the imitation of behavior, as in mirroring or mimicry of postures or gestures, which have been found to be associated with the desire to be liked by an interlocutor. Speed dating provides a unique opportunity for the study of such behavioral manifestations of interpersonal attraction through the elimination of barriers to initiating communication, while maintaining significant ecological validity. In this paper we investigate the relationship between body movement, measured via accelerometer sensors, and self-reports or ratings of attraction and affiliation in a dataset of 399 speed dates between 72 subjects. Through machine learning experiments, we found that both features derived from a single individual's body movement and features designed to measure aspects of synchrony and convergence of the couple's body movement signals were predictive of different attraction ratings. Our statistical analysis revealed that the overall increase or decrease in an individual's body movement throughout an interaction is a potential indicator of friendly intentions, possibly related to the desire to affiliate.

Accelerometers
attraction
body movement
Convergence
convergence
Feature extraction
Machine learning
non-verbal behavior
Robot sensing systems
Sensors
speed dates
synchrony
Wearable computers

http://resolver.tudelft.nl/uuid:45ad3cc9-3a64-4a39-bb77-1922f6e1a5f3

https://doi.org/10.1109/TAFFC.2021.3138349

2023-10-05

1949-3045

IEEE Transactions on Affective Computing, 14 (3), 2168-2181

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2023 J.D. Vargas Quiros, Oyku Kapcak, H.S. Hung, L.C. Cabrera Quiros