Modeling of performance and ANS activity for predicting future responses to training.

ABSTRACT

PURPOSE: Our aim was to assess whether we can predict satisfactorily performance in swimming and high frequency power (HF power) of heart rate variability from the responses to previous training. We have tested predictions using the model of Banister and the variable dose-response model. METHODS: Data came from ten swimmers followed during 30 weeks of training with performance and HF power measured each week. The first 15-week training period was used to estimate the parameters of each model for both performance and HF power. Both were then predicted in response to the training done during the second 15-week training period. The bias and precision were estimated from the mean and SD of the difference between prediction and actual value expressed as a percentage of performance or HF power at the first week. RESULTS: With the variable-dose response model, the bias for performance prediction was -0.24 ± 0.06 and the precision 0.69 ± 0.24% (mean ± between-subject SD). For HF power, the bias was 0 ± 21 and the precision 22 ± 8%. When HF power was transformed into performance using a quadratic relation in each swimmer established from the first 15-week period, the bias was 0.18 ± 0.74 and the precision 0.80 ± 0.30%. No clear trend in the error was observed during the second period. CONCLUSIONS: This study showed that the modeling of training effects on performance allowed accurate performance prediction supporting its relevance to control and predict week after week the responses to future training.