AMAB: Automated measurement and analysis of body motion

Ronald Poppe*, Sophie van der Zee, Dirk K.J. Heylen, Paul J. Taylor

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

18 Citations (Scopus)
7 Downloads (Pure)

Abstract

Technologies that measure human nonverbal behavior have existed for some time, and their use in the analysis of social behavior has become more popular following the development of sensor technologies that record full-body movement. However, a standardized methodology to efficiently represent and analyze full-body motion is absent. In this article, we present automated measurement and analysis of body motion (AMAB), a methodology for examining individual and interpersonal nonverbal behavior from the output of full-body motion tracking systems. We address the recording, screening, and normalization of the data, providing methods for standardizing the data across recording condition and across subject body sizes. We then propose a series of dependent measures to operationalize common research questions in psychological research. We present practical examples from several application areas to demonstrate the efficacy of our proposed method for full-body measurements and comparisons across time, space, body parts, and subjects.
Original languageEnglish
Pages (from-to)625-633
Number of pages9
JournalBehavior research methods
Volume46
Issue number3
DOIs
Publication statusPublished - 2014

Keywords

  • Behavior analysis
  • Automatic analysis
  • Motion capture
  • Human motion analysis
  • Measurement of body motion
  • Body motion analysis
  • HMI-MI: MULTIMODAL INTERACTIONS

Fingerprint Dive into the research topics of 'AMAB: Automated measurement and analysis of body motion'. Together they form a unique fingerprint.

Cite this