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It may sound like the invention of the heart rate monitor industry, but its a matter of scientific "fact" that HRV analyses are a great tool to monitor and manage training and recovery.

Overtraining, its existence, consequences and detection is and has always been one of the hottest topics in the fitness community. While some practitioners and trainers claim that it does not even exist, others fear it so much that they constantly undertrain. The result? Stagnation.

In the highly competitive world of the average iron-willed gymrat, its however pretty rare that the gains aint coming, cause he or she is under-training. I would guesstimate that the exact opposite is the case for at least 75% of the self-proclaimed hard-gainers. Overtraining, undereating and/or  a lack of consistency are the stumbling blocks of 99% of the trainees.

I know that you know all that, ...

... so Ill cut this short and get right to the point. Within the past two weeks I hit upon two interesting papers that describe very different, but - in both cases - effective methods to determine whether you are overtraining, or not. While I originally wanted to tackle both in one article, I had to realize that the day has only 24h for my to write and you to read SuppVersity articles. Therefore, I decided to tackle heart rate variability monitoring today and postpone writing about the other to next weeks follow up (stay tuned!).

I guess you may have heard about the usefulness of the latter on my buddy Carl Lanores Super Human Radio, already and are thus familiar with the idea that your heart’s ability to produce fluctuations in the beat-to-beat interval in response to different situations. According to José Morales and his colleagues from the Laboratory of Sport Sciences a the Ramon Llull University in Spain,

Dont turn into the guy on the left, dont overtrain & undereat | learn more

"the use of heart rate variability (HRV) as a training tool has progressively increased and deserves attention as a tool to monitor the possible states of overtraining and recovery after a training process. [...] Several studies suggest that the quantification of HRV can be used as a non-invasive method for assessing autonomic  cardiovascular  control  via  the  impact  of  HRV  on  beat-to-beat  heart  rate  modifications." (Morales. 2013)

The relationship between autonomic modulation and HRV is different during exercise and immediate recovery compared to rest periods. This makes the HRV a viable tool for the non-invasive assessment of the autonomic cardiovascular control and a comparatively objective measure of your training status (Camm. 1996; Seiler. 2007; Bosquet. 2008) .
The HRV responds particularly to heavy loads / intense workouts. The magnitude of the workout-induced stress is thought to be proportional to the activation of the sympathetic arm of the autonomic nervous system and thus the variations in autonomic balance, which can be indirectly assessed using HRV analysis (Seiler. 2007). A significantly lowered HRV days after a heavy workout is thus a signal that your central nervous system is still recovering. It tells you that youd better insert a light cardio day or spend the time with friends instead of getting back onto the grind for another torturous 5x5 session.

Technology vs. psyche - HRV vs. RESTQ-Sport

Compared to psychological tests like the Recovery Questionnaire for Athletes (RESTQ-Sport), which is frequently used in research to observe the balance between stress and recovery during training processes, the physiological data you evaluate with the HRV method is obviously more objective. It is yet still debated whether it is also reliable and can / should replace or complement the classic psychological testing procedures.

Table 1: Overview of the training weeks of the two groups (Morales. 2013)

For Morales and his colleagues this doubt was among the most important reasons to conduct a study that would integrate both methodologies. To this ends, the researchers recruited 14 male national-standard judo players (age 22.85 years; height 174.08 cm; body mass 76.85 kg) and randomized them to four-weeks of...

• high training load (HTL - 8 sessions per week ➙ short recovery periods)
• moderate training load (MTL - 4 sessions per week ➙ long recovery periods) 

For the detection of the HRV at the beginning of the first and last session in weeks 1 and 4, the researchers used a Polar S810 cardiotachometer which provided the scientists with the following parameters either directly or the corresponding data to calculate them:

Figure 1: A wide spread (green ellipse) of the poincare plot indicates full recovery.

• the mean inter-beat (RR) interval,
• the standard deviation of the inter-beat (RR) interval , 
• the heart rate & its standard deviation
• the square root of the mean squared difference of successive RR intervals, 
• the number of consecutive RRs that differed by more than 5 ms each, and 
• the percentage of consecutive RRs that differed by more than 5 ms each

That sounds extremely complicated, but in the day and age of automated data acquisition and immediate processing (including fourier transformation to get the frequency data, etc.), there are lot of tiny little gadgets and apps that can do all the hard math-work for us.

HRV + RESTQ-SPORT + HTL vs. MTL = reliable training analysis

The next thing they did was to to simply plot pairs of inter-beat intervals, e.g. 1/60 vs. 1/64, 1/64 vs. 1/76, etc. the resulting graph is a so-called poincare plot (see Figure 1) and the spread of the point in this graph can tell you whether you are well-rested (wide ellipse) or overtrained / need rest (narrow ellipse)

Figure 2: Changes in selected HRV variables, left; performance, as well as stress + recovery values in the RESTQ-Sport, right; all differences expressed relative to values at the beginning to study (Morales. 2013)

The data in Figure 2 (left) does yet demonstrate - the poincare plot of the inter-beat variables characterizes the decreased heart rate variability (HRV) quite well.

"The multivariate test indicated that there was an interaction effect between the testing time and group on HRV variables. [...] the HTL group showed lower square root of the mean squared difference for successive RR intervals, very low frequency, high frequency, short-term variability and short-range scaling exponent in the post-test than in the pre-test (p < 0.05). The HTL group showed higher low/high frequency ratio in the post-test than in the pre-test. Finally, there were no differences between the pre-test and post-test in the MTL group." (Morales. 2013)

In other words: While the HTL group showed the expected increase in HRV, the judo players in the MTL group did not experience any significant changes in heart rate variability.

The question that remains - at least until you take a look at the data in Figure 2 (right) - is: Do these abstract figures really tell me that I am overtraining? The answer the comparison to the data from the RESTQ-Sport questionnaire gives us is YES, it does!
Reference:

• Bosquet, L, et al. "Is heart rate a convenient tool to monitor over-reaching? A systematic review of the literature." British journal of sports medicine 42.9 (2008): 709-714.
• Camm, A. J., et al. "Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology." Circulation 93.5 (1996): 1043-1065.
• Morales, J., Álamo, J. M., García-Massó, X., López, J. L., Serra-Añó, P., & González, L. M. (2013). The Use Of Heart Rate Variability In Monitoring Stress And Recovery In Judo Athletes. Journal of strength and conditioning research/National Strength & Conditioning Association. 
• Seiler, Stephen, Olav Haugen, and Erin Kuffel. "Autonomic recovery after exercise in trained athletes: intensity and duration effects." Medicine and Science in Sports and Exercise 39.8 (2007): 1366.