In recent years heart rate variability (HRV) has gained popularity amongst endurance athletes as a new means of assessing the physiological state and thereby individual adaptation to training. For some, general wisdom is that Heart Rate Variability is mainly the variation in the gap between heart beats. And while that is basically true, there is of course a lot more to it that we can look at to use it. In this insight we will tackle some of the fundamental physiological principles behind HRV, how it has been used in both research and by athletes to harness athletic potential and optimize training plans and how it is incorporated in the elaborate recovery monitoring and dynamic training adjustments within the TRIQ app. So, why is HRV helpful, what on earth is heart rate variability and what is it measuring? Let’s find out.
We’ve all seen it, frustratingly: It sometimes seems that others have some sort of natural ability to do certain sports. Whilst we can park the “nature vs nurture” debate for the time being (both are of course important), there is no doubt that genetic predisposition is an important component of performance in endurance sports, and of course in order to achieve any goal, a high devotion to training and practice is also required. However, the adaptive responses to a training load or stimulus are individual, meaning that two people performing the exact same training can result in differing responses. As such, the ability to specifically tailor both the type (low or high intensity) and amount (high or low volume) of training on an individual level would be advantageous to athletes and coaching striving to achieve their endurance goals.
We are all aware of our internal innate needs. Whether it be too hot, too cold, too hungry or too full. Our body can often be stubborn, and certainly it ikes things to be a certain way. The scientific word for this desire is homeostasis, and can be defined as “the tendency towards a relatively stable equilibrium between interdependent elements, especially as maintained by physiological processes.” In essence, this refers to the ability of the body to maintain a condition of equilibrium within its internal environment. Examples include the function of the kidney, liver, skin and internal body temperature. This homeostatic regulation is often carried out by the autonomic nervous system (ANS). Many may have heard of the ANS, and simply put, it is the body’s unconscious control or our internal physiology. A good example of this is when we walk into a room where the light is bright and our pupils “automatically” dilate. This is a prime example of our ANS at work. The link between the ANS, homeostatic regulation, HRV and endurance training adaptation is a fundamental one. But before we explore the exact links, it’s important to understand that the ANS consists of another two separate systems.
The activity of the sympathetic branch causes reactions, such as the excitement of the heart (increased heart rate), constriction of blood vessels, along with reductions in gastrointestinal motility and constriction of sphincters. The sympathetic nervous system is also known as the “fight or flight response”, and it’s activated in situations involving physical or psychological stress, as adrenaline is released, increasing sympathetic activity. So, as you probably guessed, high intensity exercise really gets the SNS activated.
Conversely, the parasympathetic system is largely concerned with conservation and restoration of energy by causing a reduction in HR and blood pressure and by facilitating digestion and absorption of nutrients and discharge of waste. The PNS system is often referred to as “vagal”, due to the vagal parasympathetic nerves. Vagal tone declines with aging, and the major stimulus that increases vagal tone is regular aerobic exercise. It is important to realise that both SNS and PNS interact with one another. For example, at the onset of exercise HR will increase firstly by parasympathetic withdrawal and then by sympathetic activation. In fact, at very low levels of endurance exercise there is almost no sympathetic activation as HR is increased by parasympathetic withdrawal alone.
Taking the above into account, in the context of endurance sports, any non-invasive assessment of ANS status offers useful potential for quantifying training load, monitoring recovery and even individual adaptation to training regimes. HRV is exactly such a tool and can be used as a proxy measure of ANS activity. Heart rate variability is the variability in time between each successive heartbeat and is measured by recording the RR interval of a QRS wave during a normal electrocardiograph (ECG) trace. The R interval (Figure 1) is the point at which the ventricles of the heart contract, and pump blood around the systemic circulation. If you put your hand on your chest and feel your heart rate, that beat in the R interval. The time between consecutive heart beats is never constant, even when the heart rate seems stable. Greater variation in the RR intervals has been linked to greater dominance of the parasympathetic system and less variation more to a mix of sympathetic and parasympathetic influence. This occurs due to the parasympathetic system being faster to affect the heart. Accordingly, the gaps between beats are more varied as the change in heart rate is happening over a shorter time period, and therefore the gap between each heart beat is also changing more quickly and hence more varied. Conversely, the sympathetic system affects the heart at a much slower rate and therefore the gaps between each beat are less varied due to change occurring over a shorter time period.
Figure 1 – QRS wave with R complex
HRV can be analyzed in a variety of different ways, and the full analysis of this goes far beyond the context of this insight. However, globally methods of HRV analysis include time and frequency, domain analyses, as well as non-linear methods. Time-domain analysis is the most simple method of HRV analysis and involves plotting the R-R intervals in milliseconds (ms) against time. Frequency domain analysis quantifies the magnitude of the periodic oscillations in R-R intervals as a function of time (measured in Hz). More simply put, this looks at the frequency of change, with high frequency changing a lot, and low frequency not changing a lot. Both time and frequency domain analyses of HRV have contributed substantially to the understanding of ANS function.
The good thing is, it’s never been easier to track HRV. So for athletes, the benefit is high, with the day-to-day cost being very low. For example, HRV can easily (and accurately) be tracked using photoplethysmography (PPG) technology via the camera on smart phones, as well as other devices which measure HRV via the wrist or finger for long-term 24-hour monitoring.
At TRIQ we understand that there is a fine line between the maximization of effective training (manipulation of intensity, time and type) and ineffective training (e.g. non-functional overreaching/ overtraining). Given the fact that adaptive responses to a training load or stimulus are individual, as mentioned, it is understandable that the ability to independently assess positive or negative training adaptation would be advantageous.
For coaches and athletes a method for early detection of overtraining (OT) has been sought after for some time. Such a measure and the early detection of unwanted fatigue allows for the possibility of assuring adequate recovery through specified rest between training. At TRIQ, for example, we track a given training load of a session, and look at the recovery rate of an individual. By allowing recovery based on the constantly changing dynamic of the athlete and the amount of further training needed, the scheduled recovery optimizes future performance. Performance and also the ability of an athlete to “absorb” training begins to decline if the recovery is not adequate, resulting in excessive fatigue and even overtraining.
Many studies have examined HRV’s relation to overtraining and have revealed ambivalent findings, with increases, decreases, and no change in HRV reported. However, in one of my PhD studies, I showed substantial reductions in HRV in an NFOR elite triathlete before a competitive race and suggested that the equivocal findings in HRV studies considering over-training/excessive fatigue, may also have been due to problems with recording methodologies. This is due to day-to-day HRV values being too variable to draw meaningful conclusions; however, when HRV values were averaged over a 1-week period, the data was able to consistently showed substantially lower HRV values because of unwanted fatigue. Such findings have been subsequently supported by other research studies.
Endurance training is known to improve cardiorespiratory function and fitness in both sedentary and active individuals. For HRV, with the seen increases in cardiorespiratory function, we also see changes in cardiac vagal activity and therefore increases in HRV and decreases in resting heart rate and submaximal exercise HR. Therefore, the individualized changes in HRV can be a useful marker of training adaptations.
The changes in HRV in response to endurance training programs have been extensively studied. For example, one study showed that in people who have been sedentary or who have trained recreationally, endurance training for 2, 6 and 9 weeks has been shown to induce parallel increases in aerobic fitness and HRV. For example, previously sedentary men completed 9 weeks of intensive endurance training followed by 4 weeks of overload training and had large increases in maximal aerobic capacity (+20 %) and vagal-related HRV (+67 %).
In another one of my own studies in elite rowers at the Olympics, we showed a consistent HRV trend before peak performance, with substantial increases in HRV (above baseline) before a decline to baseline values as the competition approached (during a taper period).Such trends have since been validated in experimental studies.
Taking the above into account, as well as the versatility of HRV to track training adaptations, it stands to reason that such an index could be used as a tool to guide daily training. Fortunately this has been studied at length with positive results.
For example, one study investigated the effectiveness of using HRV to prescribe training on a day-to-day basis. Endurance runners were divided into an HRV-guided experimental training group (EXP) and one with traditional pre-defined training (TRAD). The TRAD group simply followed a traditional training program whereas the timing of moderate intensity and high intensity sessions in EXP was based on HRV measured every morning. In the EXP group the moderate and high intensity sessions were programmed if HRV was within a given individual range. Otherwise, low-intensity training was performed. At the end of the study, running performance had improved by more in the EXP group (2.1% EXP vs 1.1 TRAD), despite the EXP group doing fewer moderate and high intensity training sessions.
In a more recent study, that I was fortunate enough to be involved in, we compared an eight-week cycling training program prescribed according to either pre-defined block periodization (BP) or guided using heart rate variability (HRV). That is, subjects completed either a mixed program set out in advance or a program adjusted on a day-to-day basis via daily heart rate variability like in the previous example. The two training groups in this study ended up completing the same volume of training, with the same amount of time spent in low, moderate, and high-intensity training zones. However, while VO2max, power output at the aerobic threshold and anaerobic thresholds, and power output in a 40-min time-trial all significantly improved in the HRV-guided training group, the BP group only saw significant improvements in their power at anaerobic threshold. The data for HRV-guided training is very suggesting manipulating the session performed at a daily level in accordance with HRV has favourable effects on the adaptive response to training.
At TRIQ, HRV is very much the cornerstone of how to make decisions and individualize training on both a day-to-day and global level. The aim of using HRV and other objective AND subjective measures like athlete feedback, is to ensure every time you strap on your swim goggles, jump on your bike, or tie your running shoes, you’re maximizing the training adaptation, and getting the most out of that training session every time. Not only that, HRV allows the app to have better clarity around when to push the accelerator or step on the brakes as we fine tune every training program for the athlete.
There are exciting times ahead for athletic training and planning. The future certainly is in individualising training dynamically using more and more great wearable data insights. And HRV is just one of many!
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