The objective of exercise training is to initiate desirable physiological adaptations that ultimately enhance physical work capacity. Optimal training prescription requires an individualized approach, with an appropriate balance of training stimulus and recovery and optimal periodization. Recovery from exercise involves integrated physiological responses. The cardiovascular system plays a fundamental role in facilitating many of these responses, including thermoregulation and delivery/removal of nutrients and waste products. As a marker of cardiovascular recovery, cardiac parasympathetic reactivation following a training session is highly individualized. It appears to parallel the acute/intermediate recovery of the thermoregulatory and vascular systems, as described by the supercompensation theory. The physiological mechanisms underlying cardiac parasympathetic reactivation are not completely understood. However, changes in cardiac autonomic activity may provide a proxy measure of the changes in autonomic input into organs and (by default) the blood flow requirements to restore homeostasis. Metaboreflex stimulation (e.g. muscle and blood acidosis) is likely a key determinant of parasympathetic reactivation in the short term (0-90 min post-exercise), whereas baroreflex stimulation (e.g. exercise-induced changes in plasma volume) probably mediates parasympathetic reactivation in the intermediate term (1-48 h post-exercise). Cardiac parasympathetic reactivation does not appear to coincide with the recovery of all physiological systems (e.g. energy stores or the neuromuscular system). However, this may reflect the limited data currently available on parasympathetic reactivation following strength/resistance-based exercise of variable intensity. In this review, we quantitatively analyse post-exercise cardiac parasympathetic reactivation in athletes and healthy individuals following aerobic exercise, with respect to exercise intensity and duration, and fitness/training status. Our results demonstrate that the time required for complete cardiac autonomic recovery after a single aerobic-based training session is up to 24 h following low-intensity exercise, 24-48 h following threshold-intensity exercise and at least 48 h following high-intensity exercise. Based on limited data, exercise duration is unlikely to be the greatest determinant of cardiac parasympathetic reactivation. Cardiac autonomic recovery occurs more rapidly in individuals with greater aerobic fitness. Our data lend support to the concept that in conjunction with daily training logs, data on cardiac parasympathetic activity are useful for individualizing training programmes. In the final sections of this review, we provide recommendations for structuring training microcycles with reference to cardiac parasympathetic recovery kinetics. Ultimately, coaches should structure training programmes tailored to the unique recovery kinetics of each individual.

The measurement of heart rate variability (HRV) is often considered a convenient non-invasive assessment tool for monitoring individual adaptation to training. Decreases and increases in vagal-derived indices of HRV have been suggested to indicate negative and positive adaptations, respectively, to endurance training regimens. However, much of the research in this area has involved recreational and well-trained athletes, with the small number of studies conducted in elite athletes revealing equivocal outcomes. For example, in elite athletes, studies have revealed both increases and decreases in HRV to be associated with negative adaptation. Additionally, signs of positive adaptation, such as increases in cardiorespiratory fitness, have been observed with atypical concomitant decreases in HRV. As such, practical ways by which HRV can be used to monitor training status in elites are yet to be established. This article addresses the current literature that has assessed changes in HRV in response to training loads and the likely positive and negative adaptations shown. We reveal limitations with respect to how the measurement of HRV has been interpreted to assess positive and negative adaptation to endurance training regimens and subsequent physical performance. We offer solutions to some of the methodological issues associated with using HRV as a day-to-day monitoring tool. These include the use of appropriate averaging techniques, and the use of specific HRV indices to overcome the issue of HRV saturation in elite athletes (i.e., reductions in HRV despite decreases in resting heart rate). Finally, we provide examples in Olympic and World Champion athletes showing how these indices can be practically applied to assess training status and readiness to perform in the period leading up to a pinnacle event. The paper reveals how longitudinal HRV monitoring in elites is required to understand their unique individual HRV fingerprint. For the first time, we demonstrate how increases and decreases in HRV relate to changes in fitness and freshness, respectively, in elite athletes.

We investigated the effect of hydrotherapy on time-trial performance and cardiac parasympathetic reactivation during recovery from intense training. On three occasions, 18 well-trained cyclists completed 60 min high-intensity cycling, followed 20 min later by one of three 10-min recovery interventions: passive rest (PAS), cold water immersion (CWI), or contrast water immersion (CWT). The cyclists then rested quietly for 160 min with R-R intervals and perceptions of recovery recorded every 30 min. Cardiac parasympathetic activity was evaluated using the natural logarithm of the square root of mean squared differences of successive R-R intervals (ln rMSSD). Finally, the cyclists completed a work-based cycling time trial. Effects were examined using magnitude-based inferences. Differences in time-trial performance between the three trials were trivial. Compared with PAS, general fatigue was very likely lower for CWI (difference [90% confidence limits; -12% (-18; -5)]) and CWT [-11% (-19; -2)]. Leg soreness was almost certainly lower following CWI [-22% (-30; -14)] and CWT [-27% (-37; -15)]. The change in mean ln rMSSD following the recovery interventions (ln rMSSD(Post-interv)) was almost certainly higher following CWI [16.0% (10.4; 23.2)] and very likely higher following CWT [12.5% (5.5; 20.0)] compared with PAS, and possibly higher following CWI [3.7% (-0.9; 8.4)] compared with CWT. The correlations between performance, ln rMSSD(Post-interv) and perceptions of recovery were unclear. A moderate correlation was observed between ln rMSSD(Post-interv) and leg soreness [r = -0.50 (-0.66; -0.29)]. Although the effects of CWI and CWT on performance were trivial, the beneficial effects on perceptions of recovery support the use of these recovery strategies.