Using Heart Rate Variability (HRV) to Manage Training Load and Fatigue
One of the greatest challenges that an athlete has to overcome is effectively managing the tension between fatigue and recovery. Without applying a stimulus to cause adaptation (i.e. by training and getting tired) the body will not improve itself. On the other hand those improvements will not occur unless there is sufficient opportunity to rest (i.e. recovering from being tired). So how tired are you meant to get, and how are you meant to measure that?
Heart Rate Variability (HRV) has been used for a number of years now as a means of measuring how the nervous system is coping. If you are sitting at rest with a heart rate of 60bpm, it is undoubtedly the case that your heart is not beating once every 1,000ms (i.e. precisely once per second, every second). Rather there will be small accelerations and decelerations. The nature of these fluctuations provides information about your autonomic nervous system (ANS). An illustration of these fluctuations can be seen in figure 1.
Why does this matter? Well, because the stronger your ANS, the better your body will be able to respond to having its homeostasis disturbed, recover and improve. To put it in rather more negative terms: if you have cooked your nervous system then you can train all you like - your body will not be able to improve itself. In fact if you keep training, your body will be pushed ever further under and before long you will find yourself overtrained, utterly exhausted, and without doubt getting slower and slower.
There are various products available on the market which will provide you with feedback on how your nervous system is coping. Most of them are extremely expensive. This can be very frustrating for the serious amateur athlete. However there is a cheaper way of doing it. In fact thanks to the extraordinary generosity of Mika Tarvainen, Juha-Pekka Niskanen and the Department of Applied Physics at the University of Eastern Finland, if you have a heart rate monitor that can measure R-R intervals, it is now free. They have created the Kubios software and made it freely available - you can download it here.
As is the case with many of the articles published on this site, we are not seeking to make any objective statements. We are simply sharing the way we do it. It is fairly technical and mathematical, but if you can get your head around it it is tremendously useful. So how does it work? Well, the methodology we adopt falls into three parts:
(1) Collecting a suitable data sample;
(2) Turning the data into a series of numerical parameters;
(3) Interpreting the data.
(1) Collecting the data
We use Suunto T6 heart rate monitors, but other R-R measuring heart rate monitors would work. Immediately upon waking the athlete simply stands up, puts on his heart rate monitor, ensures he is as relaxed as possible (which should be fairly straightforward upon waking) and records a one minute heart rate log. During the minute it is important to ensure that respiration does not fall below 7 breathes per minute so we use the protocol of taking 4 seconds to breath in and 4 seconds to breath out.
Once the log as been recorded, the athlete simply transfers the file to Suunto Training Manager and then exports it as an .sdf file.
(2) Translating the data
It is at this stage that we use the Kubios software. It is remarkably straightforward. Simply import the .sdf file into the software and wait for it to process the log. It takes a couple of seconds. What you get is a display of various parameters as shown in figure 2. Simply save the results as a .pdf and then you can start analysing the data.
Fatigue is a necessary evil, but getting the right amount of it is vital.
Figure 1 (above): Although the graph averages out around 1 heart beat every second (i.e. a heart rate of 60bpm), there is actually considerably fluctuation in this example from beat to beat. At its lowest the R-R interval is about 0.9s (=67bpm) and at its highest it is about 1.16s (=52bpm).
Figure 2 (below): the data displayed by Kubios after processing a HR log. Click on the image for a larger version.
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