TITLE:
Triadic Synchrony: Application of Multiple Wavelet Coherence to a Small Group Conversation
AUTHORS:
Ken Fujiwara
KEYWORDS:
Multiple Wavelet Coherence, Nonverbal Behavior, Synchrony, Small Group, Automated Method
JOURNAL NAME:
Applied Mathematics,
Vol.7 No.14,
August
17,
2016
ABSTRACT: By applying multiple wavelet coherence
(MWC) to data from human body movements in triadic interaction, this study
quantified triadic synchrony, rhythmic similarity among three interactants.
Thirty-nine Japanese undergraduates were randomly assigned in a triad, and
engaged in a brain-storming task. Triadic synchrony was quantified by
calculating MWC to the time-series movement data collected by Kinect v2 sensor.
The existence of synchrony was statistically tested by using a pseudo-synchrony
paradigm. Results showed that the averaged value of MWC was higher in the
experimental participant trio than in those of the pseudo trio in the frequency
band of 0.5 - 1 Hz. The result supports the possible utility of applying
multiple wavelet coherence to evaluate triadic synchrony in a small group
interaction.