Towards realtime measurement of connectedness in human movement

Michael Krzyzaniak, Rushil Anirudh, Vinay Venkataraman, Pavan Turaga, Sha Xin Wei

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

2 Scopus citations


With the proliferation of wearable sensors, we have access to rich information regarding human movement that gives us insights into our daily activities like never before. In a sensor rich environment, it is desirable to build systems that are aware of human interactions by studying contextual information. In this paper, we attempt to quantify one such contextual cue - the connectedness of physical movement. Inspired by the Semblance of Typology Entrainments, we estimate the connectedness of trained dancers as observed from inertial sensors, using a diverse set of techniques such as quaternion correlation, approximate entropy, Fourier temporal pyramids, and discrete cosine transform. Preliminary experiments show that it is possible to robustly estimate connectedness that is invariant to frequency, amplitude, noise or time lag.

Original languageEnglish (US)
Title of host publicationMOCO 2015 - Proceedings of the 2nd International Workshop on Movement and Computing
Subtitle of host publicationIntersecting Art, Meaning, Cognition, Technology
PublisherAssociation for Computing Machinery
Number of pages4
ISBN (Electronic)9781450334570
StatePublished - Aug 14 2015
Event2nd International Workshop on Movement and Computing, MOCO 2015 - Vancouver, Canada
Duration: Aug 14 2015Aug 15 2015

Publication series

NameACM International Conference Proceeding Series


Other2nd International Workshop on Movement and Computing, MOCO 2015


  • Automated society
  • Automation
  • CHI
  • Connectedness
  • Correlation
  • Cross approximate entropy
  • Discrete cosine transform
  • Fourier temporal pyramids
  • Group intention
  • Group movement
  • HCI
  • Human movement
  • Social signal processing
  • Time series analysis
  • Wearable sensing

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications


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