Heart rate and heart rate variability (HRV) together provide a powerful measure of health. They respond to both physical stress and emotional strain, making them critical metrics for tracking progress and planning personalised training regimens to maximise potential improvements, alongside other key metrics. Whereas measurement was only possible in a sports physiology lab or a hospital, they are now much easier to track, with short, one minute recordings having been found to provide reliable data [1].
What makes HRV so powerful?
Most people have heard that athletes generally have lower heart rates than the rest of the population. However, HRV is much less understood. HRV is ultimately a measure of variability of the differences between successive heart beats.
The duration of the ‘R-R interval’, the time between two peaks on an ECG, will be primarily affected by energy needs of the body; when you are active, your heart beats faster in order to deliver oxygen and nutrients to your muscles.
The extent of the heart rate variability will differ between different people, depending on various factors such as genetics and the health of your autonomic nervous system. High HRV has generally been found to correlate with increased fitness [2], and positive emotional balance, whereas low HRV with stress, depression, or obesity [3,4]. Elevated physical or mental stress can result in an imbalance between sympathetic and parasympathetic activity in the nervous system, lowering HRV [5,6]. Nevertheless, the interpretation of changes in HRV is not always black and white – higher HRV is not always better, and lower HRV is not always worse, as HRV can be affected by many other factors.
The autonomic nervous system is the unconscious component of your nervous system which controls your internal body state. It consists of two components, the sympathetic system which activates the ‘fight or flight’ response, preparing the body for action in response to stress or anticipation of exercise (e.g. by releasing adrenaline and noradrenaline resulting in increased heart rate, contractility, and blood pressure), and the parasympathetic system which mediates calm and relaxation, having inverse effects, and aiding recovery. Heart rate provides a direct measure of whether the sympathetic or parasympathetic system is active, whereas HRV is understood to provide a measure of the balance of autonomic activity by revealing the interactions between the two systems [6].
A healthy and balanced nervous system will be able to increase and decrease heart rate more appropriately in response to external stressors, leading to increased HRV. A tired or stressed nervous system will struggle to respond in this way, generally resulting in lower HRV. HRV has been found to accurately predict performance of athletes [2], as well as predicting patient recovery from heart attacks, congestive heart failure [3], and even depression [4].
How can athletes use HRV?
For an athlete, increases and decreases in HRV can represent positive and negative adaptation to training, and it can help determine their recovery status, as well as susceptibility to illness or injury [5]. For example, although overreaching can help athletes improve, pushing oneself too hard leads to non-functional overreaching, or, in extreme cases, overtraining, which can result in reduced performance lasting weeks or months; reduced HRV following higher training loads can help an athlete recognise that they are pushing themselves too hard before doing too much damage to their body. HRV can help to prove wrong the myth that training harder and longer will always lead to better results.
By adapting your training regimen in response to HRV readings, you can maximise improvement. HRV-guided training has been shown to be more effective for improving performance in endurance exercise than pre-planned training [8,9]. However, regular and consistent data collection is key. Adjusting training load should not necessarily be in response to one or two unexpected HRV measurements, as this can be a product of natural fluctuation, unless other metrics also highlight concerns. Instead, long-term trends should be identified and used to inform decisions as part of a more holistic picture of the athlete’s well-being. There is significant variation between individuals and understanding your HRV fingerprint requires sufficient data [5]. Daily measurement of HRV has been shown to be an effective method for monitoring athletes [7], we hence recommend that you measure HRV every morning. If your recordings are outside of your normal range for too many days in a row, you might want to consider limiting training intensity and focussing on recovery.
Summary
Heart rate and HRV can be accurately and reliably monitored with just a one minute daily smartphone recording, and is responsive to both physical and mental stress, providing an insight into the health of your autonomic nervous system. Consistent and regular data collection of heart rate, HRV, and other key metrics, can allow for informed adjustments to be made to lifestyle or training load in order to optimise performance.
Measuring HRV
You can read more about our tips on how to measure morning HRV accurately here.
Further Reading
Understanding your body is important for shaping your training, and we recommend that you keep on learning about what these metrics can tell you, and what they can’t. You can find out more about the science of HRV with some of the links below.
HRV Course: Heart Rate Variability vs Heart Rate
Science for Sport: Heart Rate Variability
TriathlonWorld: 9 Myths about measuring heart rate variability
References
1 Flatt AA, Esco MR. (2015) Heart rate variability stabilisation in athletes: towards more convenient data acquisition. Clin Physiol Funct Imaging, 36(5):331-6. https://doi.org/10.1111/cpf.12233
2 Dong JG. (2016) The role of heart rate variability in sports physiology. Exp Ther Med, 11(5): 1531-1536. https://dx.doi.org/10.3892%2Fetm.2016.3104
3 Billman GE. (2011). Heart Rate Variability – A Historical Perspective. Front Physiol, 2: 86. https://dx.doi.org/10.3389%2Ffphys.2011.00086
4 Kemp AH, Quitana DS, Gray MA, Felmingham KL, Brown K, Gatt JM. (2010). Impact of depression and antidepressant treatment on heart rate variability: a review and meta-analysis. Biol Psychiatry, 67(11): 1067-74. https://doi.org/10.1016/j.biopsych.2009.12.012
5 Plews DJ, Laursen PB, Stanley J, Kilding AE, Buchheit M. (2013). Training Adaptation and Heart Rate Variability in Elite Endurance Athletes: Opening the Door to Effective Monitoring. Sports Med, 43: 773-781 https://doi.org/10.1007/s40279-013-0071-8
6 Taelman J, Vandeput S, Spaepen A, Van Huffel S. (2009). Influence of Mental Stress on Heart Rate and Heart Rate Variability. 4th European Conference of the International Federation for Medical and Biological Engineering, 1366-1369. https://doi.org/10.1007/978-3-540-89208-3_324
7 Flatt AA, and Esco MR. (2016). Evaluating Individual Training Adaptation with Smartphone-Derived Heart Rate Variability in a Collegiate Female Soccer Team. The Journal of Strength and Conditioning, 30(2): 378-385. https://doi.org/10.1519/JSC.0000000000001095
8 Kiviniemi, A.M., Hautala, A.J., Kinnunen, H., and Tulppo, M.P. (2007). Endurance training guided individually by daily heart rate variability measurements. European Journal of Applied Physiology, 101(6): 743-751. https://doi.org/10.1007/s00421-007-0552-2
9 Botek, M., McKune, A.J., Krejci, J., Stejskal, P., and Gába, A. (2013). Change in Performance in Response to Training Load Adjustment Based on Autonomic Activity. International Journal of Sports Medicine, 35(6), 482-488. https://doi.org/10.1055/s-0033-1354385
10 Peng RC, Zhou XL, Lin WH, Zhang YT. (2015). Extraction of Heart Rate Variability from Smartphone Photoplethysmograms. Computational and Mathematical Methods in Medicine, vol. 2015, Article ID 516826, 11 pages. https://doi.org/10.1155/2015/516826
11 Plews DJ, Scott B, Altini M, Wood M, Kilding AE, Laursen PB. (2017). Comparison of Heart-Rate-Variability Recording With Smartphone Photoplethysmography, Polar H7 Chest Strap, and Electrocardiography. Human Kinetics, 12(10): 1324-1328. https://doi.org/10.1123/ijspp.2016-0668