Predicting daily recovery during long-term endurance training using machine learning analysis.

Journal: European journal of applied physiology
PMID: 38900201

Abstract

PURPOSE: The aim of this study was to determine if machine learning models could predict the perceived morning recovery status (AM PRS) and daily change in heart rate variability (HRV change) of endurance athletes based on training, dietary intake, sleep, HRV, and subjective well-being measures.

Authors

  • Jeffrey A Rothschild
    Sports Performance Research Institute New Zealand (SPRINZ), Auckland University of Technology, Auckland, New Zealand. Jeffrey.Rothschild@aut.ac.nz.
  • Tom Stewart
    a Sport Performance Research Institute New Zealand , AUT University , Auckland , New Zealand.
  • Andrew E Kilding
    Sports Performance Research Institute New Zealand (SPRINZ), Auckland University of Technology, Auckland, New Zealand.
  • Daniel J Plews
    Sports Performance Research Institute New Zealand (SPRINZ), Auckland University of Technology, Auckland, New Zealand.

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