Body Movement Synchrony Predicts Degrees of Information Exchange in a Natural Conversation.

body movement synchrony exchanging information motion energy analysis natural conversation optical motion capture system

Journal

Frontiers in psychology
ISSN: 1664-1078
Titre abrégé: Front Psychol
Pays: Switzerland
ID NLM: 101550902

Informations de publication

Date de publication:
2020
Historique:
received: 13 11 2019
accepted: 02 04 2020
entrez: 16 5 2020
pubmed: 16 5 2020
medline: 16 5 2020
Statut: epublish

Résumé

Human interaction has two principle functions: building and maintaining relationships with others and exchanging information. The function of building and maintaining relationships with others relates to interpersonal coordination; this behavior pattern is expected to predict the outcome of social relationships, such as between therapists and patients. It is unclear, however, whether the exchange of information is associated with interpersonal coordination. In the present study, we tested a hypothesis of whether body movement synchrony occurs in a natural conversation and whether this synchrony has a positive correlation with the degree of information exchange. Fifty participants were engaged in a conversation task; each had different roles in the conversation. We measured their body movements during this conversation using an optical motion capture system. Similar to methods that can be found in previous research, we calculated body movements and quantified their synchrony applying the methods previously reported that automatically quantified their body movements. Moreover, we determined the participants' degree of information exchange concerning the conversation using a questionnaire. We observed that the body movement synchrony of pairs who talked with each other was significantly higher than that of pairs who did not talk with each other, and that this synchrony was positively associated with the degree of information exchange. These results suggest that body movement synchrony predicted information exchange.

Identifiants

pubmed: 32411064
doi: 10.3389/fpsyg.2020.00817
pmc: PMC7201108
doi:

Types de publication

Journal Article

Langues

eng

Pagination

817

Informations de copyright

Copyright © 2020 Tsuchiya, Ora, Hao, Ono, Sato, Kameda and Miyake.

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Auteurs

Ayaka Tsuchiya (A)

School of Computing, Tokyo Institute of Technology, Yokohama, Japan.

Hiroki Ora (H)

School of Computing, Tokyo Institute of Technology, Yokohama, Japan.

Qiao Hao (Q)

School of Computing, Tokyo Institute of Technology, Yokohama, Japan.

Yumi Ono (Y)

School of Computing, Tokyo Institute of Technology, Yokohama, Japan.

Hikari Sato (H)

School of Computing, Tokyo Institute of Technology, Yokohama, Japan.

Kohei Kameda (K)

Department of Computer Science, Tokyo Institute of Technology, Yokohama, Japan.

Yoshihiro Miyake (Y)

School of Computing, Tokyo Institute of Technology, Yokohama, Japan.

Classifications MeSH