• DocumentCode
    677399
  • Title

    A novel bio-kinematic encoder for human exercise representation and decomposition - Part 1: Indexing and modelling

  • Author

    Saiyi Li ; Caelli, Terry ; Ferraro, Mario ; Pathirana, Pubudu N.

  • Author_Institution
    Fac. of Sci. & Technol., Deakin Univ., Geelong, VIC, Australia
  • fYear
    2013
  • fDate
    25-28 Nov. 2013
  • Firstpage
    24
  • Lastpage
    29
  • Abstract
    Current bio-kinematic encoders use velocity, acceleration and angular information to encode human exercises. However, in exercise physiology there is a need to distinguish between the shape of the trajectory and its execution dynamics. In this paper we propose such a two-component model and explore how best to compute these components of an action. In particular, we show how a new spatial indexing scheme, derived directly from the underlying differential geometry of curves, provides robust estimates of the shape and dynamics compared to standard temporal indexing schemes.
  • Keywords
    biology computing; biomechanics; estimation theory; acceleration information; angular information; biokinematic encoder; decomposition; differential geometry; execution dynamics; exercise physiology; human exercise representation; robust estimate; spatial indexing scheme; standard temporal indexing scheme; trajectory; two-component model; velocity information; Hidden Markov models; Indexing; Mathematical model; Noise; Shape; Trajectory; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control, Automation and Information Sciences (ICCAIS), 2013 International Conference on
  • Conference_Location
    Nha Trang
  • Print_ISBN
    978-1-4799-0569-0
  • Type

    conf

  • DOI
    10.1109/ICCAIS.2013.6720524
  • Filename
    6720524