Q - Power

Indoor Rowing Team

Fatigue (4)

Having identified values for certain variables, in order to make any sense of the figures they need to be compared against something. There are two ways of doing this, both of which are potentially of use.

First, a comparison can be drawn against what is considered to be "normal". The difficulty is determining quite what "normal" is. There has been a certain amount of work undertaken in this field. In 1996 the Taskforce of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology produced "Normal Values of Standard Measures of HRV". The Taskforce considered  long-term readings should be taken over 24 hours and short term readings over a period of 5 minutes (in a supine position). The longer reading, which is not practical for day to day fatigue monitoring, is not necessary if one is prepared to disregard VLF power (and therefore disregard circadian and hormonal influences).

Although an anecdotal observation, we have found that 5 minute readings do not appear obviously different from 1 minute readings in a standing position, although it has to be accepted that in those circumstances it is better to take parasympathetic data from RMSSD rather than from a time domain analysis. Indeed 1 minute readings show far greater consistency from breath to breath than the longer readings. Despite our preference for 1 minute readings, the standard short term (5 minute) HRV measurements as determined by the Taskforce are set out opposite. 

One thing that has become apparent from looking at the HRV data of highly trained athletes (resting HR in the low 40s or high 30s; rowing between 5,000km and 9,000km per annum) is that they are anything but "normal". For example, whereas normal total power might be in the range 2,500msto 4,500ms2 in a supine position, we have recorded figures above 5,000ms2 whilst standing in an athlete who is extremely fatigued, and above 25,000msin a rested athlete. What is the best way of dealing with these admittedly predictable results; "admittedly" because exercise improves the resilience of the ANS thereby improving HRV results - one would expect heavily trained individuals to have good numbers.

We address the issue by building an HRV profile for each athlete who is using the protocol (we are more concerned about nervous system fatigue with our athletes who are rowing 9,000km per annum than those on 5,000km). It takes a few weeks to build such a profile (it is useful to use a 4 week mesocycle as a minimum) but a range defining that athletes version of "normal" becomes reasonably apparent arising from the ordinary training program manipulation of exercise intensity, duration and therefore total load. Note the different data profiles on the right of this page for two different Q-Power athletes.

The more data points that are recorded for the athlete, the more significant future outlying data points become. So if an athlete records an RMSSD above 50ms 90% of the time, three consecutive morning readings of 35 requires a response (or at least an acknowledgment on the part of the coach that the athlete is tired for it may be that the coach is trying to provoke significant short term fatigue). Where the data really becomes invaluable is if after a short period of rest or light training (e.g. a couple of days), the readings are still not great. Whereas without the data the temptation might be to train hard again, better progress might in fact be made by holding intensity down for another day or so. There is a good illustration of overtraining here if you want to know what you should be looking for.

There are clearly certain limitations to the system. HRV is sensitive. If you are woken in the morning by a 4 year old stamping on your face (this is not a hypothetical example) then trying to get some meaningful HRV data after 20 minutes of negotiating terms with the trespasser will be impossible. But provided the data is not used to the exclusion of common sense, it works tremendously well. 

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1996 Task Force Normal Values (5 minute test; supine)

              Total Power: 3466 ± 1018 (ms2)
              LF:                1170 ± 416 (ms2)
              HF:                975 ± 203 (ms2)
              LF/HF ratio:   1.5-2.0 


Nunan, Sandercock and Brodie identified in 2010 from a review of some 44 studies between 1997 and 2008 involving  a total of over 21,000 participants that actual there was enormous inter-individual variations in HRV data (especially with regard to spectral analysis) and that there was a need for a large scale population study. They also identified figures generally lower than that found by the taskforce. 

Using data obtained from Q-Power athletes we have derived our own sense of what might be described as normal. However given the ranges are dependent on the individual, we are expressing the data by sample athlete (60 second test; standing), providing an average figure and 1 standard deviation.

      Athlete 1
           Mean HR:        62.3 (SD=   3.5)
           SDNN:  92.8 (SD= 22.1)
           RMSSD:          62.0 (SD= 19.3)                 
           Total Power: 7938 (SD=4393)
           LF (n.u.):  96.6 (SD=   1.8)
           HF (n.u.):    3.4 (SD=   1.8)

      Athlete 2
           Mean HR:        60.2 (SD=   6.4)
           SDNN:        131.9 (SD= 27.7)
           RMSSD:                141.5 (SD= 34.4)                 
           Total Power:       22103 (SD=8599)
           LF (n.u.):  90.1 (SD=   3.1)
           HF (n.u.):    9.9 (SD=   3.1)



What to look for in your own data

Mean HR: the lower the better.

SDNN: the higher the better, indicating greater HRV as a whole.

RMSSD: the higher the better, indicating a stronger para-sympathetic nervous system.

Total Power: the higher the better, indicating greater HRV as a whole.

If you collect data over a period of time you can rapidly establish the sorts of numbers that are typical for you when rested and when tired. "Better" (as used above) means better rested and/or a stronger nervous system.

Click here for a good illustration of what overtraining looks like.
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