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Utilizing a Novel 2D Image Processing System for Relating Body Composition Metrics to Performance in Collegiate Female Rowers

Author

Listed:
  • Michael R. Esco

    (Exercise Physiology Laboratory, Department of Kinesiology, University of Alabama, Tuscaloosa, AL 35487, USA)

  • Clifton J. Holmes

    (Exercise Physiology Laboratory, Department of Kinesiology, University of Alabama, Tuscaloosa, AL 35487, USA)

  • Katherine Sullivan

    (Exercise Physiology Laboratory, Department of Kinesiology, University of Alabama, Tuscaloosa, AL 35487, USA)

  • Bjoern Hornikel

    (Exercise Physiology Laboratory, Department of Kinesiology, University of Alabama, Tuscaloosa, AL 35487, USA)

  • Michael V. Fedewa

    (Exercise Physiology Laboratory, Department of Kinesiology, University of Alabama, Tuscaloosa, AL 35487, USA)

Abstract

The purpose of this study was to determine if rowing performance was associated with fat mass (FM) or fat-free mass (FFM) measured using a novel 2D digital image analysis system. Nineteen female rowers (ages = 20.3 ± 1.0 years, weight = 73.8 ± 8.3 kg, height = 172.7 ± 4.7 cm) participated in this study. FM and FFM were estimated with a smartphone application that uses an automated 2D image analysis program. Rowing performance was measured using a 2 km (2k) timed trial on an indoor ergometer. The average speed of the timed trial was recorded in raw units (m·s −1 ) and adjusted for body weight (m·s −1 ·kg −1 ). FFM was significantly correlated to unadjusted 2k speed (r = 0.67, p < 0.05), but not for FM (r = 0.44, p > 0.05). When 2k speed was adjusted to account for body weight, significant correlations were found with FM (r = −0.56, p < 0.05), but not FFM (r = −0.34, p > 0.05). These data indicate that both FM and FFM are related to rowing performance in female athletes, but the significance of the relationships is dependent on overall body mass. In addition, the novel 2D imaging system appears to be a suitable field technique when relating body composition to rowing performance.

Suggested Citation

  • Michael R. Esco & Clifton J. Holmes & Katherine Sullivan & Bjoern Hornikel & Michael V. Fedewa, 2021. "Utilizing a Novel 2D Image Processing System for Relating Body Composition Metrics to Performance in Collegiate Female Rowers," IJERPH, MDPI, vol. 18(5), pages 1-9, March.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:5:p:2413-:d:508633
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