[Via Athletic Lab] A Closer Look at Heart Rate Variability

This content was originally posted on athleticlab.com

[This is a guest blog by Gaby Smith. Gaby Smith completed her MS in Exercise Science at Northeastern University and is participating in the Athletic Lab Mentorship Program. Gaby is a Certified Strength and Conditioning Specialist and holds certifications with U.S. Soccer, USAW, and USTFCCCA.]

Resting, exercise, and recovery heart rates are common measures used to monitor fatigue, fitness, and performance responses and are often used to adjust training load. Recently, heart rate variability (HRV) has become a measure more commonly used to assess an athlete’s readiness to perform and ensure the appropriate dose of training (ie. preventing overtraining or detraining). Generally, training load is quantified by external and internal indicators of intensity along with training time. External indicators may include distance, power output, or number of repetitions, while internal indicators include oxygen uptake, heart rate, blood lactate, or RPE (Buchheit, 2014).

When it comes to monitoring and measuring athletes’ fatigue, heart rate (HR) measures are commonly used because they are inexpensive, time efficient, and can be applied routinely and simultaneously with many athletes. Resting HR, exercise HR, and HRV are all related to autonomic nervous system (ANS) activity and their use in combination may improve the monitoring of the training status of athletes. While there are a number of HR measures that can be used to assess an athlete’s training status, it is of utmost importance that whatever measure is used, it is standardized in order to isolate the training-induced effects (Buccheit, 2014).

Physiological determinants of resting HR include cardiac muscle morphology, ANS activity, body position, and plasma volume (Buccheit, 2014). Best practice recommends the athlete measure resting HR upon waking up in the morning from a supine, seated, or standing position – but the position should be consistent across measurements. Exercise HR is another commonly used and easy to measure assessment of training status. Because HR is closely related to oxygen uptake during continuous exercise, exercise HR can be used to measure relative exercise intensity. There are correlations between decreases in exercising HR and improvements in high-intensity exercise performance.

Recently, HRV has become a measure of increasing interest and has been more commonly used for tracking the adaptation or maladaptation of athletes to training. HRV measures beat-to-beat differences in HR and is thought to reflect the cardiac regulation by the ANS. While previously used to predict sudden cardiac death and disease progression, recent studies have demonstrated that HRV is also useful in exercise training. These studies have reflected that HRV can be used as a marker of the sympathetic or vagal component of the ANS and can track the course of training adaptation to assist in setting optimal training loads to improve performance (Dong, 2016).

What is HRV?

HRV refers to the variations in the time between successive heart beats (time between consecutive R-R intervals) and is a result of the two competing branches of the ANS: the sympathetic and parasympathetic nervous systems. HRV can be measured using an electrocardiogram (ECG), fitness tracker, smartphone app, or heart rate strap. Along with being used to assess training status, HRV has been used in a medical context where it has been shown to be a predictor of mortality and incidents of sudden cardiac death (Bigger, 1992).

High HRV means the body is responsive to both sympathetic and parasympathetic inputs and is capable of adapting and responding to training. Low HRV indicates that one branch of the ANS is dominant (usually the sympathetic) and is usually associated with stress, fatigue, dehydration, etc. (Dong, 2016).

HRV is affected by mental stressors, not just physical stressors such as competition or training. Work-related stress, having to make difficult decisions, public speaking, and performing tests or exams have all been shown to reduce HRV (Dong, 2016; Taelman, 2004).

What is a “Good” HRV?

While a higher HRV is generally a sign of better fitness, HRV is highly individualized and differs between individuals. Age, gender, fitness level, environment, and genetics must all be taken into account when looking at an individual’s HRV. Younger people tend to have higher HRV than older people, and males tend to have higher HRV than females. Athletes tend to have higher HRV than non-athletes or sedentary individuals (Buccheit, 2014).

When monitoring HRV, it is important to track individual trends, rather than comparing HRV between individuals. With training, HRV should increase, and a downward trend may be a sign of overtraining, fatigue, or stress (Dong, 2016).

Training and HRV

HRV has become one of the most used training and recovery monitoring tools because autonomic regulation is an important indicator of training adaptations and the body’s responsiveness to training (Aubert, 2003). Heart rate is primarily controlled through the activity of the ANS, which is comprised of the sympathetic and parasympathetic nerves. The sympathetic nervous system causes the body to respond in stressful environments (training, games, competitions, etc.) by secreting epinephrine and norepinephrine and increasing HR, contractility, and blood pressure to increase blood flow to the muscles. The parasympathetic nervous system does the opposite; it reduces heart rate and blood pressure in the absence of stress. The parasympathetic nervous system helps facilitate recovery after a stressful event by counteracting the effects of the sympathetic nervous system. Therefore, both the sympathetic and parasympathetic nervous systems are critical for performance and recovery. An imbalance between the two systems can lead to a reduction in performance.

Because HRV reflects ANS function and stress, it is frequently used to identify when training is optimal and monitor recovery status and the potential for overtraining. Research has suggested that HRV can (Aubert, 2003):

  • Reflect recovery status
  • Help determine overtraining
  • Identify an athlete’s ability to adapt and respond to training
  • Aid in training prescription
  • Potentially predict susceptibility to illness or injury

HRV-Guided Training

The concept of using HRV-guided training is perhaps one of the most useful applications when discussing HRV. This idea uses HRV to prescribe the intensity of a given training session. If the athlete had an average or above average HRV, they would be prescribed an intense training session. When the athlete’s HRV is below normal, they would be prescribed a lower-intensity session. Because there will be inter-athlete variability in baseline HRV, it is important to prescribe intensity based on each athlete’s HRV relative to their baseline rather than comparing absolute HRV between athletes.

One study found that HRV-guided training improved running performance and maximal running velocity more so than pre-planned training (Kiviniemi, 2007). Another study found a relationship between high HRV scores with improved VO2max, while those with low HRV scores were found to have reduced VO2max (Hedelin, 2001). These findings suggest HRV-guided training may be more beneficial in improving aerobic performance than traditional pre-planned training. While the effectiveness of HRV-guided training in regard to strength development is not as conclusive, it appears that athletes with above baseline HRV scores are more sensitive to performance gains than those with lower HRV scores.
HRV and Recovery

Many studies have cited a reduction in HRV following intense training. One study found a reduction in HRV in the 24-hours following a high intensity strength training session. HRV returned to baseline after 72 hours of recovery, indicating a relationship between HRV and recovery (Chen, 2011). Another study found that HRV increased during an intense training period and decreased over an overload training phase. After two weeks of recovery, HRV rebounded and increased above baseline, indicating that intense training may actually improve HRV (Pichot, 2002). There have also been studies to determine the relationship between HRV and injury. While this relationship requires further investigation, it is thought that the correlation between low HRV and fatigue or stress would lead the athlete to be more susceptible to injury.

Key Takeaways:

  • HRV is the variation in time between successive heart beats
  • High HRV scores are suggested to indicate greater ability to adapt to training stress and improve performance
  • HRV-guided training appears to induce greater performance gains than pre-planned training programs
  • HRV is correlated with recovery status

References

  • Aubert AE, Seps B, Beckers F. Heart rate variability in athletes. Sports Med. 2003;33(12):889-919.
  • Bigger JT Jr; Fleiss JL; Steinman RC; Rolnitzky LM; Kleiger RE; Rottman JN. (1992). “Frequency domain measures of heart period variability and mortality after myocardial infarction”. Circulation. 85 (1): 164–171.
  • Buchheit M. Monitoring training status with HR measures: do all roads lead to Rome?. Front Physiol. 2014;5:73. Published 2014 Feb 27. doi:10.3389/fphys.2014.00073
  • Chen, J-L, Yeh, D-P, Lee, J-P, Chen, C-Y, Huang, C-Y, Lee, S-D, Chen, C-C, Kuo, TBJ, Kao, C-L, and Kuo, C-H. Parasympathetic nervous activity mirrors recovery status in weightlifting performance after training. J Strength Cond Res 25(6): 1546–1552, 2011.
  • Dong GJ. The role of heart rate variability in sports physiology. Exp Ther Med. 2016 May; 11(5): 1531–1536.
  • Hedelin, R., Bjerle, P., & Henriksson-Larsen, K. (2001) Heart Rate Variability in athletes: relationship with central and peripheral performance. Medicine & Science in Sports & Exercise, 33(8), 1394-1398.
  • Kiviniemi, A.M., Hautala, A., Kinnumen, H., & Tulppo, M. (2007) Endurance training guided by daily heart rate variability measurements. European Journal of Applied Physiology, 101: 743-751.
  • Pichot, V., T. Busso, F. Roche, M. Garet, F. Costes, D. Duverney, J. R. Lacour, And J. C. Barthe´Le´My. Autonomic Adaptations To Intensive And Overload Training Periods: A Laboratory Study. Med. Sci. Sports Exerc., Vol. 34, No. 10, Pp. 1660–1666, 2002.
  • Taelman J, Vandeput S, Spaepen A, and Van Huffel S. Influence of Mental Stress on Heart Rate and Heart Rate Variability. Eur J Appl Physiol. 2004 Jun;92(1-2):84-9.

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