Heart rate variability (HRV) as an indicator of recovery

Heart rate variability (HRV) has changed from a laboratory measure into a figure that watches, rings and chest sensors show every morning. It is called a ‘readiness index’ for training. The editorial team looked into what HRV actually measures, how to collect the data so that it makes sense, and how not to turn it into an object of excessive anxiety.

What HRV is and what it reflects

The heart of a healthy person at rest does not beat like a metronome. The intervals between adjacent beats (the so-called RR or NN intervals) constantly change by tens of milliseconds. These fluctuations are what is called heart rate variability. High variability at rest is, as a rule, a sign of a well-regulated and adaptive system.

The main regulator of these fluctuations is the autonomic nervous system. The parasympathetic branch, through the vagus nerve, slows the rhythm and acts very quickly, from beat to beat, which is why it provides most of the short-term variability. The sympathetic branch speeds up the rhythm and acts more slowly.

The classic document that standardised the measurement of HRV was the recommendations of the task force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology (1996). It described the methods of calculation, the physiological interpretation and the clinical application of the indicator.

For an athlete HRV is interesting because an intense load, sleep deprivation, illness, psychological stress and alcohol usually reduce parasympathetic activity at rest. Accordingly, morning HRV can reflect how far the body has recovered from the cumulative stress of the previous days.

At the same time HRV is an indirect measure. It measures neither the state of the muscles, nor glycogen stores, nor tissue damage. It shows the state of cardiac regulation, which only partly reflects overall recovery.

Indicators: RMSSD, SDNN, frequency indices

There are many ways to calculate HRV. The review by Shaffer and Ginsberg (2017) systematises them into time-domain, frequency-domain and nonlinear. For daily monitoring of athletes the time-domain indicator RMSSD is most often used — the square root of the mean squared differences between adjacent intervals.

RMSSD reflects parasympathetic activity well, is stable in short recordings (1–5 minutes) and is less sensitive to breathing rate than the frequency indicators. Because of the uneven distribution of values it is often log-transformed (lnRMSSD), which makes statistical analysis easier.

Different devices show HRV differently: some show raw RMSSD in milliseconds, others their own ‘index’ or readiness score. It is not worth comparing data from different brands with each other; it is important to look at the dynamics within a single device and method.

Absolute HRV values are highly individual and depend on age, genetics and level of fitness. One athlete’s high HRV does not make them ‘better recovered’ than another with a lower one. Only the change relative to your own baseline matters.

How to measure correctly

The best time to measure is immediately after waking, before coffee, food and checking messages. The person should empty the bladder, adopt the same position (lying or sitting) and record for 1–5 minutes at rest, breathing naturally.

Chest sensors recording the ECG signal are considered more accurate than optical sensors on the wrist. Night measurements, taken by rings and watches, are convenient and stable, but reflect something slightly different — the average state during sleep, not the morning one. Both approaches are acceptable provided you use one and the same method consistently.

• Measure every day, or at least 3–5 times a week under the same conditions.
• Use one body position and one device.
• Record subjective data alongside: sleep quality, mood, muscle pain, fatigue.
• Mark special circumstances: illness, alcohol, a flight, stress.
• For the first 2–4 weeks simply collect data for the baseline.

Plews and co-authors (2013) showed that individual daily HRV values are very ‘noisy’ and can fluctuate without obvious reasons. Therefore a 7-day rolling average is more reliable. It is precisely the weekly trend that is better connected with changes in fitness than a single morning measurement.

It is also worth determining an individual ‘normal’ range of fluctuation — for example, the average value over recent weeks plus or minus a certain fraction of the standard deviation. Changes within this range are considered noise, and going beyond it a signal to pay attention.

How to interpret the data

A one-day drop in HRV after a hard workout is a normal reaction. Parasympathetic activity recovers gradually, and after intense sessions this can take from a few hours to a day or two. The review by Stanley, Peake and Buchheit (2013) describes how the duration of this recovery depends on the intensity and duration of the load.

A prolonged, multi-day drop in the weekly average below the usual range, against a background of fatigue, poor sleep and declining results, is a reason to reduce the load or add a rest day. Especially if the resting heart rate rises in parallel.

An interesting scenario is when HRV rises excessively against a background of worsening well-being. In some athletes, especially in endurance sports, a paradoxical increase in parasympathetic indicators has been described under severe overwork. Buchheit (2014) emphasised that HRV must always be analysed in the context of the load, well-being and results.

Several studies tested training ‘by HRV’. Kiviniemi and co-authors (2007) compared a standard plan with a plan in which intense workouts were carried out only when morning HRV was normal or elevated, and light ones when it was reduced. The group with individualised planning achieved a greater gain in aerobic performance. Subsequent works have generally confirmed that such an approach can be no worse or better than standard planning.

Plews and co-authors (2013), in a review for Sports Medicine, described a practical model for using HRV to monitor elite endurance athletes: regular measurements, a rolling average, individual ranges and combination with other indicators.

Limitations and common mistakes

HRV is sensitive to many factors unconnected with training: alcohol, a late heavy dinner, dehydration, heat, the menstrual cycle, psychological stress, the onset of an infection. This is at once an advantage (it shows the overall load on the body) and a drawback (it is hard to understand the cause of a change).

A common mistake is to make decisions based on a single morning value. The second is to compare your HRV with other people or with ‘norms’ from the internet. The third is excessive anxiety: a daily fixation on the figure can itself become a stressor, worsen sleep and, as a result, lower HRV.

HRV is not a medical diagnostic tool in the hands of a user. Unusual readings, an irregular pulse, ‘skipped’ beats or a device notification about a possible arrhythmia require a doctor’s consultation and an ECG, not self-interpretation.

It is also important to remember the effect of some drugs and stimulants: beta-blockers, thyroid medications, caffeine and pre-workout complexes can change the heart rate and HRV, so changes against their background are interpreted with caution.

Editorial conclusions

HRV mainly reflects the parasympathetic regulation of the heart and can serve as a useful indirect indicator of recovery from cumulative stress.

For monitoring it is better to use RMSSD, to measure under the same conditions in the morning or at night, and to be guided by the 7-day rolling average relative to your own normal range, rather than by a single value.

HRV works best in combination with the resting heart rate, well-being, sleep quality and training indicators. The figure by itself should not dictate all decisions.

The editorial team also advises reading our materials on how much an athlete should sleep, on active recovery and on the signs of overtraining.

References

1. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Circulation. 1996;93(5):1043–1065.
2. Shaffer F, Ginsberg JP. An overview of heart rate variability metrics and norms. Front Public Health. 2017;5:258.
3. Plews DJ, Laursen PB, Stanley J, Kilding AE, Buchheit M. Training adaptation and heart rate variability in elite endurance athletes: opening the door to effective monitoring. Sports Med. 2013;43(9):773–781.
4. Buchheit M. Monitoring training status with HR measures: do all roads lead to Rome? Front Physiol. 2014;5:73.
5. Kiviniemi AM, Hautala AJ, Kinnunen H, Tulppo MP. Endurance training guided individually by daily heart rate variability measurements. Eur J Appl Physiol. 2007;101(6):743–751.
6. Stanley J, Peake JM, Buchheit M. Cardiac parasympathetic reactivation following exercise: implications for training prescription. Sports Med. 2013;43(12):1259–1277.