Mean stability and between-session reliability of cycling biomechanics variables in elite pursuit cyclists

Daniel Williams*, Marcus Dunn, Paul Worsfold, Deborah Newton, Steve H. Faulkner, Francesca d'Andrea, Jon Wheat

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The purpose of this study was to determine the number of crank revolutions required to obtain stable mean values of sagittal plane biomechanics variables, and the between-session reliability of these variables, whilst cyclists used an aerodynamic position. Eighteen elite cyclists completed a 3-min maximal bout on a cycling ergometer. Lower-limb kinematic and kinetic data were captured using 2D motion capture and force pedals. Raw data were filtered using a 4th order Butterworth low-pass filter (6 hz) and interpolated to 100 points per revolution. The middle 60 revolutions of each trial were extracted and 37 discrete and 15 time-series variables were calculated. Mean stability was assessed in all participants, and between-session reliability was analysed in a subset of 11 participants. Sequential averaging indicated more revolutions to stability than iterative intra-class correlation coefficients. Crank kinetics were more stable than joint kinematics and kinetics. For stable discrete and time-series variables, 30 and 38 revolutions are recommended, respectively. Between-day reliability for all variables was moderate to excellent, and good to excellent for crank kinetics and joint kinematics variables. Hip flexion-extension and ankle dorsiflexion kinetics were least reliable. Researchers and applied practitioners should consider these findings when planning, and interpreting results from, cycling biomechanics interventions.
Original languageEnglish
Article number2471805
JournalSports Biomechanics
Early online date3 Mar 2025
DOIs
Publication statusE-pub ahead of print - 3 Mar 2025

Keywords

  • Biomechanics
  • cycling
  • reliability
  • intraclass correlation coefficient
  • sequential averaging

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