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Endurance training 4: Day-to-day monitoring so you know that go-time is go-time
In the last blog we talked about the specific value of low-intensity training sessions, and why making sure these sessions are truly physiologically easy such that our key high-intensity workouts can be performed to the best of our ability in order to generate the largest stimulus for adaptation to training. If our low-intensity training sessions drift over that aerobic threshold we mentioned towards the anaerobic threshold, we experience physiological stress that will, in time, reduce our capacity for high-intensity training the next day. One of the specific stresses we see when low-intensity exercise creeps above the aerobic threshold is an acute disturbance in our nervous system (6).
This particular stress, its measurement via what is called ‘heart rate variability’ or HRV, and how we can apply HRV measurements within our daily training decisions is going to be the subject of this fourth endurance training blog. At Elevate Coaching, we advocate for the use of HRV as a practical tool in the management of serious endurance training for maximising performance and wellbeing.
What is heart rate variability?
Heart rate variability (HRV) is a tricky concept to get your head round. HRV refers to the variation in time between-heart beats. If we have a heart rate of 60 beats per minute, our heart is of course beating on average once per second. However, in reality, even with a heart rate of 60 beats per minute, our heart does not beat exactly once every second. It will beat, there might be a 1.2-second gap before the next beat, then a 0.7-second gap, then a 0.9-second gap, then another 1.2-second gap. This evens out to once every second on average, but you can see there is considerable variability in the time between-beats when we look at this data at a beat-to-beat level. HRV is the measurement of this variability (4).
Why is this interesting? Well, HRV tells us about our physiological stress through the degree of activation in the two branches of our autonomic nervous system; the sympathetic and parasympathetic nervous systems. The autonomic nervous system is the link between the brain and many largely unconscious basic bodily functions, like digestion, breathing, and heart rate. The sympathetic nervous system acts to dial things up in times of stress, so increases heart rate, whereas the parasympathetic nervous system acts to slow things down, so is important in recovery from things like hard exercise.
When we are sympathetically stressed, such as in the aftermath of a hard workout or race, our HRV is low, so beat-to-beat intervals are very consistent. When we are well-recovered and so have low levels of physiological stress, our HRV is higher, making the beat-to-beat intervals less consistent. Therefore, measuring our HRV gives us an indication of the degree of physiological stress we are under (1, 4). When we are performing serious amounts of endurance training, whilst also dealing with work stress, life stress, late nights, early mornings, and disrupted schedules, tracking our HRV, and therefore physiological stress, can be useful when manipulating our training on a day-to-day level. High levels of sympathetic stress in the long-term can and will lead to more globalised fatigue, non-functional overreaching, and, the enemy to success of all endurance athletes, overtraining (4). This will eventually manifest as a down-turn in our ability to train, perform, and recover, and almost certainly ensure that we do not achieve our goals on race-day.
Integrating HRV into endurance training: A decision tree
HRV has seen significant interest in the scientific literature, and as such can now be measured as easily as with a smartphone by opening an app and pressing a finger over the camera upon waking each morning (5). There are a range of applications through which this can be done, with, in my opinion, the best and most user-friendly being ‘HRV4Training’ (see link: https://www.hrv4training.com/). Now, it is important to note that I personally have no specific relationship with HRV4Training, so I am not saying this in order to sell you a product (the app costs about $17). This is the app that I personally use, that I use in my scientific research, and that I recommend to athletes because of how it integrates quite sophisticated measures and analyses from your heart rate trace to produce user-friendly recommendations that can be linked to other training-related software such as TrainingPeaks.
The app will give you a daily recovery score and training recommendation, while the raw and more detailed data can also be viewed through the app and shared with an eagle-eyed coach. We like to use HRV to track trends in physiological stress over time, such that we can act to prevent any down-turn in performance and wellbeing before it manifests in our training. So, if an athlete wakes up with high levels of physiological stress and therefore low HRV from a previous workout, significant work stress, or poor night of sleep, they can decide to postpone their planned high-intensity 6 x 6-minute suffer-fest in favour of a day of easy, low-intensity training that will give them the recovery they need to perform the high-intensity workout well the following day. HRV responses are also a very good way of letting us know if our low-intensity sessions designed to be performed below the aerobic threshold are actually of low-intensity, or if the power and pace of these sessions needs to be reduced to achieve the low-intensity goal and facilitate recovery. HRV gives us empirical data with which to make these decisions.
We like to use the data according to the following decision tree:
![Heart Rate Variability Decision Tree.001.jpeg](https://images.squarespace-cdn.com/content/v1/5a2f80e9dc2b4a10d22b008c/1577037291378-I4FW31561GBKS1HDHA22/Heart+Rate+Variability+Decision+Tree.001.jpeg)
Fig. 1. Decision tree showing how to use daily, resting HRV measurements to manipulate training at a day-to-day level.
What do the studies show?
A number of studies have recently looked at whether using HRV in essentially this way translates into improved training and performance adaptations, with the balance of evidence looking favourably on HRV-guided training compared to traditionally prescribed blocks of training (2, 3). For instance, a study published this year and led by Alejandro Javaloyes from the University of Elche in Spain recruited trained male cyclists and had them perform a battery of endurance performance tests and took a range of physiological measurements prior to a four-week baseline training phase and eight-week intervention training phase, where their training programme was either set-in-stone from the outset or manipulated on a day-to-day level by HRV (2). Important markers of endurance performance such as the power at anaerobic threshold and average power during a maximal-effort 40-min time-trial improved in the HRV-guided training group, but not the traditional training group. These and other results provide compelling evidence for the use of HRV within endurance training programmes, and no doubt many more studies in this area will be conducted and studies in the coming months and years.
Summary
In summary, serious endurance training wilfully places great physiological stress on the body. It is very common, however, for the stresses of endurance training to build and build over time, especially when the training intensity discipline we discussed in the previous blog is not executed well. If this stress does mount over time, we are likely to see non-functional overreaching and overtraining, which will greatly hamper our ability to train well, our performance, and our wellbeing. A simple minute-long measurement of heart rate variability each morning using a smartphone can help us manage this stress, and let us know if go-time is go-time on that high-intensity workout we had planned, or if it would be instead better the push the workout and suck in some more low-intensity training and recovery, such that we are ready to crush the workout the next day. HRV gives us empirical data with which to make these decisions.
References
1. Buchheit M. Monitoring training status with HR measures: Do all roads lead to Rome? Front Physiol 5: 73, 2014.
2. Javaloyes A, Sarabia JM, Lamberts RP, Moya-Ramon M. Training prescription guided by heart-rate variability in cycling. Int J Sports Physiol Perform 14: 23–32, 2019.
3. Javaloyes A, Sarabia JM, Lamberts RP, Plews DJ, Moya-Ramon M. Training prescription guided by heart-rate variability vs. block periodization in well-trained cyclists. J. Strength Cond. Res. .
4. 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. Sport Med 43: 773–781, 2013.
5. Plews DJ, Scott B, Altini M, Wood M, Kilding AE, Laursen PB. Comparison of heart-rate-variability recording with smartphone photoplethysmography, polar H7 chest strap, and electrocardiography. Int J Sports Physiol Perform 12: 1324–1328, 2017.
6. Seiler S, Haugen O, Kuffel E. Autonomic recovery after exercise in trained athletes: Intensity and duration effects. Med Sci Sports Exerc 39: 1366–1373, 2007.