Modeling and quantitative measurement method of the tripartite interpersonal distance dynamics for children with ASD

Airi Tsuji, Takuya Enomoto, Soichiro Matsuda, Jyun'ichi Yamamoto, Kenji Suzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, We focused on the measurement method of the tripartite interpersonal distance in the social development supporting for children with autism spectrum disorder (ASD), and tried quantitatively measurements of interpersonal distance dynamics between three-person using motion capture. We report on the modeling and measurement about the tripartite interpersonal distance dynamics.

Original languageEnglish
Title of host publicationComputers Helping People with Special Needs - 16th International Conference, ICCHP 2018, Proceedings
PublisherSpringer Verlag
Pages523-526
Number of pages4
ISBN (Print)9783319942766
DOIs
Publication statusPublished - 2018 Jan 1
Event16th International Conference on Computers Helping People with Special Needs, ICCHP 2018 - Linz, Austria
Duration: 2018 Jul 112018 Jul 13

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10896 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other16th International Conference on Computers Helping People with Special Needs, ICCHP 2018
CountryAustria
CityLinz
Period18/7/1118/7/13

Keywords

  • ASD
  • Interpersonal distance
  • Motion capture

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Tsuji, A., Enomoto, T., Matsuda, S., Yamamoto, J., & Suzuki, K. (2018). Modeling and quantitative measurement method of the tripartite interpersonal distance dynamics for children with ASD. In Computers Helping People with Special Needs - 16th International Conference, ICCHP 2018, Proceedings (pp. 523-526). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10896 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-94277-3_81