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Related Experiment Video

Updated: Jun 4, 2025

Determining The Electromyographic Fatigue Threshold Following a Single Visit Exercise Test

Determining The Electromyographic Fatigue Threshold Following a Single Visit Exercise Test

Published on: July 27, 2015

Differentiating acute fatigue and overreaching during intensified training using a recursive least squares algorithm

Thierry Busso¹, Sébastien Chalencon²

¹Laboratoire Interuniversitaire de Biologie de la Motricité, Université Jean Monnet Saint-Etienne, Lyon 1, Université Savoie Mont-Blanc, EA 7424, F-42023, Saint-Etienne, France. busso@univ-st-etienne.fr.

European Journal of Applied Physiology

|December 22, 2024

Summary

A time-varying model can identify overreaching in swimmers by analyzing performance changes after training. This helps coaches adjust training loads to prevent overtraining and optimize performance.

Keywords:

Fatigue Mathematical model Physiological adaptation Sports performance Swimming

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Area of Science:

Sports Science
Exercise Physiology
Biomechanical Modeling

Background:

Overtraining syndrome is a significant concern in elite sports, impacting athlete performance and health.
Distinguishing between acute fatigue and functional overreaching is crucial for effective training periodization.

Purpose of the Study:

To evaluate a variable dose-response model for its ability to detect overreaching during intensified training in swimmers.
To assess if a time-varying model can account for dynamic changes in training load and performance.

Main Methods:

A time-varying model with a recursive least squares algorithm was applied to 61 weeks of data from eight swimmers.
Daily training load (pool and dry land) and bi-weekly 50m performance trials were recorded.
Model impulse responses were calculated weekly to assess performance changes after training sessions.

Main Results:

Functional overreaching was identified by performance declines during intensified training, followed by recovery during reduced training.
The time-varying model provided distinct markers differentiating overreaching from acute fatigue.
Increased training load showed an increased acute negative effect and decreased delayed positive effect on performance.

Conclusions:

Weekly model parameter variations can diagnose overreaching by tracking acute and delayed training effects.
This model-derived information can assist practitioners in adjusting training plans to prevent overreaching and optimize swimmer performance.