I am going to apply the same logic we use for why we assess movement (to influence program design) with monitoring the function of the autonomic nervous system (ANS); if you’re not assessing the ANS, you’re guessing.

If you’re unfamiliar with what the ANS is and why it’s important I suggest you read this. In a nutshell the ANS governs “rest and digest” and “fight or flight” responses in the body. This is done without our conscious control. The two components of the ANS are the parasympathetic branch and sympathetic branch. Sympathetic activity is elevated in response to stress be it physical, or mental. Adrenaline is secreted and catabolic activity (the breakdown of structures) ensues. Parasympathetic activity is elevated in the absence of stress and functions to heal and repair the body.

We can monitor our ANS status non-invasively and inexpensively through heart rate variability (HRV). I explain how you can do this here.

HRV as an indicator of autonomic function can tell you a tremendous amount about your athlete’s responsiveness to training. I shared plenty of research in this post that lends support to HRV as an effective tool for; reflecting recovery status, showing better adaptation to training and even predicting performance. In a separate post I shared my thoughts on HRV as a predictor for injury.

Let me summarize what I shared in my initial research review post;

HRV reflects recovery status in elite Olympic weightlifters (Chen et al 2011), national level rowers (Iellamo et al 2004) and untrained athletes (Pichot et al 2002).

Cipryan et al (2007) showed that hockey players performed better when HRV was high while performance was rated lower when HRV was low.

Endurance athletes who improved vo2 max had consistently high HRV while athletes who did not improve vo2 max had low HRV (Hedelin et al 2001).

Endurance athletes who trained using HRV to determine their training loads had a significantly higher maximum running velocity compared to athletes in a pre planned training group (Kiviniemi et al 2007, Kiviniemi et al 2010).

Female athletes who used HRV to guide their training increased their fitness levels to the same level as females in a pre planned training group but the HRV group had fewer high intensity training days (Kiviniemi et al 2010).

(references for the above articles can be found in my original post here.

I’d now like to show some more research that lends support to the usefulness of HRV in monitoring athletes.

Mourot, L (2004) saw decreased HRV in overtrained aerobic athletes. Uusitalo et al (2000) also saw decreased HRV in overtrained female aerobic athletes.

Huovinen et al (2009) measured HRV and testosterone to cortisol (T-C) ratio in army recruits during their first week of basic training. The training was class room based (not physical) and therefore all stress can be considered mental. The authors found that HRV declined in several soldiers, though not all. This demonstrates that, what can be interpreted as stress is highly variable and dependent on the individual. The authors used the terms “high responders” and “low responders” to describe the differences among soldiers. Immediately I thought about the differences among athletes and how their bodies perceive stress. You can’t assume everyone is responding in kind to a training program. What is stressful for one athlete may not be as stressful to another.

All soldiers that showed decreases in HRV also showed lower T-C ratios. In contrast, soldiers with higher HRV had higher T-C ratio’s. Baseline T-C levels were not recorded so we shouldn’t draw any concrete conclusions however it appears that low HRV (increased sympathetic activity with parasympathetic withdrawl) is associated with a reduced T-C ratio.

Hellard et al. (2011) found that in national level swimmers, as HRV dropped (sympathetic predominance) there was an increased risk of illness. The drops in HRV that lead to illness were preceded by a sudden increase in parasympathetic activity the week prior to illness. The authors speculated that the preceding increase in HRV (parasympathetic/vagal activity) was a reflection of the body experiencing the first incubation period and that an increase in vagal activity was a protective response trying to modulate the magnitude of early immune responses to inflammatory stimuli. The subsequent increase in sympathetic activity and decrease in HRV occurs during the symptomatic phase of the illness.

In humans, increased sympathetic activity is generally associated with inflammatory responses while parasympathetic predominance actually inhibits inflammation. At this point in time I will not elaborate on this for the simple fact that I don’t fully understand it. However, we can speculate that if we’re seeing consistently low HRV scores in ourselves or our athletes there is probably an increase in inflammation occurring. Check out Thayer (2009) for more information regarding HRV and inflammation. Simon from iThlete sent me that paper and I’m still processing it.

When dealing with a team or if we train multiple athletes at the same time we need to be aware of how they are adapting and recovering from training. Work by Hautala et al (2001) shows that athletes will recover from exercise at different rates according to fitness levels (obviously). Basically, fit individuals recover faster and show less HRV fluctuation compared to less fit individuals. In a team setting, some individuals who are highly fit may not be getting a sufficient training stimulus while other athletes who are less fit can be overworked.

Kiviniemi et al (2010) found that females take longer to recover from aerobic training than males. This needs to be considered if you are training a mixed gender group.

Buchheit et al (2009) and Manzi et al (2009) both found HRV to be a predictor of aerobic performance.

I’m well aware that the development of athletes has been taking place without the use of HRV monitoring. There are many great coaches and trainers who have their own systems and methods of monitoring recovery in their athletes that work well.

HRV is a tool to use within your own systems. I have thoughts about how I would implement this in a team setting that I will share another time.

To truly autoregulate the training of ourselves or of athletes, we need as much information about present physiologic status as possible. Based on the research and my own personal experience with HRV, this technology takes much of the guesswork out of load/volume manipulation and training prescription. Training hard when HRV is low can be counterproductive and delay recovery. Training hard when HRV is chronically low can lead to illness, injury, overtraining syndrome and suppressed testosterone. Alternatively, increasing load/volume on days when HRV is high can lead to more favourable adaptation. HRV can tell us how stressful the training was for our athletes based on how long it takes HRV to reach baseline in subsequent days. HRV can indicate how much stress your athlete is experiencing outside of training. There are several indications one can take from a simple HRV measurement. Further research will reveal more correlation between HRV and sports performance.

I believe that to train an athlete optimally, we need to be assessing the state of the autonomic nervous system… otherwise we’re guessing.

References:

Buchheit, M. et al (2009) Monitoring endurance running performance using cardiac parasympathetic function. European Journal of Applied Physiology, DOI 10.1007/s00421-009-1317-x

Hellard, P., et al. (2011) Modeling the Association between HR Variability and Illness in Elite Swimmers. Medicine & Science in Sports & Exercise, 43(6): 1063-1070

Huovinen, J. et al. (2009) Relationship between heart rate variability and the serum testosterone-to-cortisol ratio during military service. European Journal of Sports Science, 9(5): 277-284

Kiviniemi, A.M., Hautala A.J., Kinnunen, H., Nissila, J., Virtanen, P., Karjalainen, J., & Tulppo, M.P. (2010) Daily exercise prescription on the basis of HR variability among men and women. Medicine & Science in Sport & Exercise, 42(7): 1355-1363.

Manzi, V. et al (2009) Dose-response relationship of autonomic nervous system responses to individualized training impulse in marathon runners. American Journal of Physiology, 296(6): 1733-40

Mourot, L. et al (2004) Decrease in heart rate variability with overtraining: assessment by the Poincare plot analysis. Clinical Physiology & Functional Imaging, 24(1):10-8.

Thayer, J. (2009) Vagal tone and the inflammatory reflex. Cleveland Clinic Journal of Medicine, 76(2): 523-526

Uusitalo, A.L.T., et al (2000) Heart rate and blood pressure variability during heavy training and overtraining in the female athlete. International Journal of Sports Medicine, 21(1): 45-53