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J Sports Med Phys Fitness. 2017 Jun;57(6):907-915. doi: 10.23736/S0022-4707.16.06322-2. Epub 2016 Mar 11.

Interpreting daily heart rate variability changes in collegiate female soccer players.

Author information

1
Department of Kinesiology, Exercise Physiology Laboratory, University of Alabama, Tuscaloosa, AL, USA - aflatt@crimson.ua.edu.
2
Human Performance Laboratory, Auburn University at Montgomery, Montgomery, AL, USA - aflatt@crimson.ua.edu.
3
Department of Kinesiology, Exercise Physiology Laboratory, University of Alabama, Tuscaloosa, AL, USA.
4
Human Performance Laboratory, Auburn University at Montgomery, Montgomery, AL, USA.
5
Department of Physical Education, State University of Londrina, Londrina, Brazil.
6
High Performance Sport New Zealand, Auckland, New Zealand.
7
Department of Sport and Recreation, Waikato University, Hamilton, New Zealand.
8
Sports Performance Research Institute New Zealand (SPRINZ), Auckland University of Technology, Auckland, New Zealand.

Abstract

BACKGROUND:

Heart rate variability (HRV) is an objective physiological marker that may be useful for monitoring training status in athletes. However, research aiming to interpret daily HRV changes in female athletes is limited. The objectives of this study were: 1) to assess daily HRV (i.e., log-transformed root mean square of successive R-R interval differences, lnRMSSD) trends both as a team and intra-individually in response to varying training load (TL); and 2) to determine relationships between lnRMSSD fluctuation (coefficient of variation, lnRMSSDcv) and psychometric and fitness parameters in collegiate female soccer players (N.=10).

METHODS:

Ultra-short, Smartphone-derived lnRMSSD and psychometrics were evaluated daily throughout 2 consecutive weeks of high and low TL. After the training period, fitness parameters were assessed.

RESULTS:

When compared to baseline, reductions in lnRMSSD ranged from unclear to very likely moderate during the high TL week (effect size ±90% confidence limits [ES±90% CL] =-0.21±0.74 to -0.64±0.78, respectively) while lnRMSSD reductions were unclear during the low TL week (ES±90% CL=-0.03±0.73 to -0.35±0.75, respectively). A large difference in TL between weeks was observed (ES±90% CL=1.37±0.80). Higher lnRMSSDcv was associated with greater perceived fatigue and lower fitness (r [upper and lower 90% CL]=-0.55 [-0.84, -0.003] large, -0.65 [-0.89, -0.15] large).

CONCLUSIONS:

Athletes with lower fitness or higher perceived fatigue demonstrated greater reductions in lnRMSSD throughout training. This information can be useful when interpreting individual lnRMSSD responses throughout training for managing player fatigue.

PMID:
26997322
DOI:
10.23736/S0022-4707.16.06322-2
[Indexed for MEDLINE]

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