• DocumentCode
    3304322
  • Title

    Signal processing for estimating energy expenditure of elite athletes using triaxial accelerometers

  • Author

    Wixted, Andrew ; Thiel, David ; James, Daniel ; Hahn, Allan ; Gore, Christopher ; Pyne, David

  • Author_Institution
    Center for Wireless Monitoring & Applications, Griffith Univ., Brisbane, Qld.
  • fYear
    2005
  • fDate
    Oct. 30 2005-Nov. 3 2005
  • Abstract
    Fitness development of elite athletes requires an understanding of physiological factors such as athlete energy expenditure (EE). For athletes involved in football at the elite level, it is necessary to understand the energy demands during competition to develop training regimes. By identifying an appropriate EE estimator in triaxial accelerometer data, in conjunction with identifying sources of inter-athlete variance in that estimator, signal processing was developed to extract the estimator. In this system, low-power signal processing was implemented to extract both the EE estimator and other information of physiological and statistical interest
  • Keywords
    accelerometers; biomechanics; medical signal processing; sport; athlete energy expenditure; energy expenditure estimator; fitness development; signal processing; triaxial accelerometers; Accelerometers; Australia; Biomedical monitoring; Cyclic redundancy check; Data mining; Heart rate measurement; Legged locomotion; Mechanical sensors; Micromechanical devices; Signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Sensors, 2005 IEEE
  • Conference_Location
    Irvine, CA
  • Print_ISBN
    0-7803-9056-3
  • Type

    conf

  • DOI
    10.1109/ICSENS.2005.1597820
  • Filename
    1597820