• DocumentCode
    628281
  • Title

    Towards estimation of front-crawl energy expenditure using the wearable aquatic movement analysis system (WAMAS)

  • Author

    Dadashi, Farzin ; Aminian, Kamiar ; Crettenand, Florent ; Millet, Gregoire P.

  • Author_Institution
    Laboratory of Movement Analysis and Measurement, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
  • fYear
    2013
  • fDate
    6-9 May 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Inertial measurement unit (IMU) is a promising tool in the quantification of energy expenditure for human on-land activities, though has never been deployed before to calculate the aquatic activities energy expenditure. Investigating the factors that influence the required energy in aquatic locomotion can help the biomecanicians to better understand the biophysics of swimming. We used a set of three waterproofed IMUs worn on the forearms and sacrum of twelve swimmers to estimate the front-crawl energy expenditure. The swimmers performed three 300-m trials at 70%, 80% and 90% of their 400-m personal best time. At the end of each 300-m the reference value of energy expenditure was measured based on indirect calorimetry and blood lactate concentration. The three IMUs were used to extract the main spatio-temporal determinants of the front-crawl energy expenditure. Extraction of these parameters using IMU was previously validated. We used a combination of a linear estimator and kernel smoother on the residuals of the linear part to derive the mapping between the spatio-temporal inputs and reference energy expenditure. The algorithm validation on test data shows a strong association between the estimated and reference energy expenditure (Spearman´s rho = 0.97, p-value <0.001) and a high relative precision of 9.7%.
  • Keywords
    Acceleration; Blood; Calibration; Energy measurement; Estimation; Feature extraction; Kernel; Energy expenditure; coordination; frontcrawl; velocity; wearable sensor;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Body Sensor Networks (BSN), 2013 IEEE International Conference on
  • Conference_Location
    Cambridge, MA, USA
  • ISSN
    2325-1425
  • Print_ISBN
    978-1-4799-0331-3
  • Type

    conf

  • DOI
    10.1109/BSN.2013.6575467
  • Filename
    6575467