Predicting Maximal Military Occupational Task Performance from Physical Fitness Tests Using Machine Learning.

Journal: Medicine and science in sports and exercise
Published Date:

Abstract

PURPOSE: Optimal performance in military tasks is crucial for operational success. These tasks are often simulated in training, assessing personnel performance within a military environment. However, these assessments are time-consuming and a potential injury risk. Physical characteristics such as muscular strength, power, aerobic endurance, and circumferences can be used to predict these dynamic and demanding tasks. Utilizing machine learning models to predict assessment outcomes may lead to optimized management of personnel, time, and interventions in the military.

Authors

  • Ayden McCarthy
  • Jodie Anne Wills
  • Joel Thomas Fuller
  • Steve Cassidy
    School of Computing, Macquarie University, Macquarie Park, NSW, AUSTRALIA.
  • Brad C Nindl
    Department of Sports Medicine and Nutrition in the School of Health and Rehabilitation Sciences, University of Pittsburgh, Neuromuscular Research Laboratory/Warrior Human Performance Research Laboratory, Pittsburgh, PA.
  • Tim L A Doyle