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Frauendorfer, D., Mast, M.S., Nguyen, L. and Gatica-Perez, D. (2014) Nonverbal Social Sensing in Action: Unobtrusive Recording and Extracting of Nonverbal Behavior in Social Interactions Illustrated with a Research Example. Journal of Nonverbal Behavior, 38, 231-245.
http://dx.doi.org/10.1007/s10919-014-0173-5

has been cited by the following article:

• 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.