Monitoring Training With Heart-Rate Variability: How Much Compliance Is Needed for Valid Assessment?

Purpose: To establish the minimum number of days that heart-rate-variability (HRV, ie, the natural logarithm of square root of the mean sum of the squared differences between R-R intervals, Ln rMSSD) data should be averaged to achieve correspondingly equivalent results as data averaged over a 1-wk period. Methods: Standardized changes in Ln rMSSD between different phases of training (normal training, functional overreaching (FOR), overall training, and taper) and the correlation coefficients of percentage changes in performance vs changes in Ln rMSSD were compared when averaging Ln rMSSD from 1 to 7 d, randomly selected within the week. Results: Standardized Ln rMSSD changes (90% confidence limits, CL) from baseline to overload (FOR) were 0.20 +/- 0.28, 0.33 +/- 0.26, 0.49 +/- 0.33, 0.48 +/- 0.28, 0.47 +/- 0.26, 0.45 +/- 0.26, and 0.43 +/- 0.29 on days 1 to 7, respectively. Correlations (90% CL) over the same time sequence and training phase were -.02 +/- .23, -.07 +/- .23, -.17 +/- .22, -.25 +/- .22, -.26 +/- .22, -.28 +/- .21, and -.25 +/- .22 on days 1 to 7. There were almost perfect quadratic relationships between standardized changes/r values vs the number of days Ln rMSSD was averaged (r(2) = .92 and .97, respectively) in trained triathletes during FOR. This indicates a plateau in the increase in standardized changes/r values' magnitude after 3 and 4 d, respectively, in trained triathletes. Conclusion: Practitioners using HRV to monitor training adaptation should use a minimum of 3 (randomly selected) valid data points per week.