A pilot study using entropy as a non-invasive assessment of running

Andrew Murray, Joong Ryu, John Sproule, Anthony Turner, Philip Graham-Smith, Marco Cardinale

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Purpose: Running performance is influenced by the interaction of biomechanical and physiological factors. Miniaturised accelerometers worn by the athlete can be used to quantify mechanical aspects of running and be used as a non-invasive tool to assess training status and progression. The aim of this study was to define and validate a method to assess running regularity and allow the estimation of an individual’s V̇O2 and/or blood lactate [La]b based on data collected with accelerometers and heart rate (HR). Methods: Male adolescent endurance athletes completed an incremental submaximal aerobic stage test where V̇O2 and [La]b were measured. The test was terminated when [La]b concentration at the end of the stage exceeded 4 mmol/L. Two wireless tri-axial accelerometers were placed on the right shank and lower back throughout the test. The Root Mean Square (RMS) and the Sample Entropy (SampEn) were calculated for the vertical (VT), medial-lateral (ML) and anterior-posterior (AP) components of acceleration. Results: There were significant positive correlations of acceleration and entropy variables with [La]b and V̇O2, with moderate to high coefficients (r = 0.43 – 0.87). RMS of the shank acceleration was the most highly related with both physiological variables. When the accelerometer was attached on the trunk, SampEn of the VT acceleration had the strongest relationship with V̇O2 (r = 0.76, P < 0.01). Conclusions: The described method of analysis of running complexity may allow an assessment of gait variability which tracks non-invasively V̇O2 and/or [La]b allowing monitoring of fatigue or training readiness for trained adolescent individuals.
Original languageEnglish
Pages (from-to)1119-1122
Number of pages4
JournalInternational Journal of Sports Physiology and Performance
Issue number8
Early online date17 Jan 2017
Publication statusPublished - Sept 2017

Keywords / Materials (for Non-textual outputs)

  • accelerometry
  • regularity
  • lactate
  • aerobic
  • gait


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