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What is Machine Learning for Endurance Recovery Prediction about?

This study investigates the use of machine learning models to predict perceived morning recovery status (AM PRS) and daily heart rate variability (HRV change) in endurance athletes based on various factors including training, diet, sleep, and subjective well-being. Over 12 weeks, data from 43 athletes were analyzed, revealing that group-level predictions were more accurate than baseline models, although individual accuracy varied significantly. The findings suggest that while common variables can effectivel

Author

Ng Hui Hwa

Language

EN