A novel method of determining the active drag profile in swimming via data manipulation of multiple tension force collection methods

Alex Haskins, Carla McCabe, Rodney Kennedy, Ruairi McWade, Alex Lennon, Dominic Chandar

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Abstract

A novel method aimed at evaluating the active drag profile during front-crawl swimming is proposed. Fourteen full trials were conducted with each trial using a stationary load cell set-up and a commercial resistance trainer to record the tension force in a rope, caused by an athlete swimming. Seven different stroke cycles in each experiment were identified for resampling time dependent data into position dependent data. Active drag was then calculated by subtracting resistance trainer force data away from the stationary load cell force data. Mean active drag values across the stroke cycle were calculated for comparison with existing methods, with mean active drag values calculated between 76 and 140 N depending on the trial. Comparing results with established active drag methods, such as the Velocity Perturbation Method (VPM), shows agreement in the magnitude of the mean active drag forces. Repeatability was investigated using one athlete, repeating the load cell set-up experiment, indicating results collected could range by 88 N depending on stroke cycle position. Variation in results is likely due to inconsistencies in swimmer technique and power output, although further investigation is required. The method outlined is proposed as a representation of the active drag profile over a full stroke cycle.

Original languageEnglish
Article number10896
Pages (from-to)1-13
Number of pages14
JournalScientific Reports
Volume13
Issue number1
Early online date5 Jul 2023
DOIs
Publication statusPublished online - 5 Jul 2023

Bibliographical note

Funding Information:
The authors would like to thank all study participants and coaches for their contribution to the study. The authors would also like to thank Ulster University, British Swimming, Ben Scott and Oliver Logan of British Swimming, Swim Ireland, Kevin McGuigan of Swim Ireland, Lisburn City Swimming Club, Stephen Yamin-ali, Ryan Keating and Trainesense/PoolShark for their expertise and support throughout the study. The authors would also like to thank those who helped with result collection during the main experiment.

Funding Information:
The authors would like to thank and acknowledge funding from the Department for the Economy that made this study possible.

Publisher Copyright:
© 2023, The Author(s).

Keywords

  • Data acquisition
  • Engineering
  • Fluid dynamics
  • Scientific data

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