Thursday, April 1, 2021

Case studies (check back for updates)

Case 1:

This is a quick and dirty look at a ramp done from data sent to me by a reader. I have no info except this:

I did 4 min steps and increased 10w each step. FTP is about 200, max HR is around 190. I was a bit nervous so HR felt a tad high at the start, then was about right when I hit 200w. 

I do have a fit file with power data and the HRV logger with RR. The artifacts were well below 5%. I did two plots - HR vs DFA a1 and DFA a1/Power over time.

Let's see how they look:

DFA a1 vs HR - this one is easy to do and interpret - simply plot DFA a1 vs HR from a DFA a1 of .5 (or lower) to about 1, in Excel and look at the intersection:

  • HR at the "HRVT" is about 162 bpm

Power calculation can be more difficult - here we need to get the power on the same graph. I did that by synchronizing the timestamps. Then did regression lines for the entire power data, but a regression only for the marked DFA a1:

  • The HRVT is about 175 watts.
  • For those who don't want to do this, find the power for the average heart rate computed in HR vs DFA a1 - they should be close.

HRV Logger:


  •  HRVT HR about 168

 

Conclusion:

  • Good looking ramp
  • HRV logger data was quite close to Kubios


Case #2 (5/23/21):

This is a data set done with a Polar H10, HRV logger recording and lactate measurements.  I show this as a good example of how even lactate readings can be confusing and don't necessarily help as much as one thinks.  Also we will see that HRV logger a1 values are quite close to Kubios.

The ramp - cycling with steps of 25 watts every 5 minutes with lactate values at the step end.
What we see here is that a1 passed the .75 boundary just above a HR of 135 bpm, by inspecting the numbers.  Although this is every 5 min data, if we were using HRV logger, real time, we would have a solid guess that between a HR of 135 -144, we are passing the AeT.
 
How does HRV logger do compared to Kubios.  Since I don't have the pre processed RR intervals, I compared the Logger a1 (already artifact cleaned) to the Kubios a1 directly (no artifact correction in Kubios).
  • How does it look?  Very good!
  • Not perfect but Logger does capture the general outline well.

HRVT HR
 
Here are the graphs of HR vs a1 with two ways of doing so - a short vs longer data plot:

  • Both lines look reasonable, but you can see that a few bpm difference is present.
  • One is not necessarily "better" than the other. 

 
What about lactate and the LT1
Here we get into the real conundrum - what threshold do we use - loglog, first linear change, 1 mmol rise etc.  I plugged the numbers into the Newell template in R and this is what we have:
From the Newell article:
LT definition -
Traditionally, the lactate threshold was determined
subjectively from plots of the lactate concentration
versus work rate by visually identifying the treadmill
velocity or work rate that best corresponds to a
departure from a linear baseline pattern. Lundberg,
Hughson, Weisiger, Jones, and Swanson (1986)
proposed fitting a linear spline where the lactate
threshold is the estimated work rate corresponding to
the location of the knot (i.e. the point of intersection
between the two linear splines). The location of the
knot and the parameters of the lines are estimated by
minimizing the sum of the squared differences
between the observed lactate values and the fitted
values.

Log-log definition -
A log transformation of both the work rate and
blood lactate concentration has been suggested
(LTloglog) in an attempt to gain a better estimate of
the lactate threshold (Beaver et al., 1985).
The 1 mmol rise is self explanatory.

This particular athlete has values of 147, 126, 146 bpm for the three accepted methods.
Note that our HRVT is right in the middle of these.
Is one better than the other?  I couldn't say.  
Only note that things are not as black and white as they may sound in review articles.

Bottom line here:
  • HRV logger is close to Kubios premium in accuracy.
  • Even lactate testing is open to interpretation and argument on what constitutes the LT1.
  • Some variability will occur in the HRVT just by plotting - but a few bpm should not be a deal breaker.
  • In this case the HRVT sits between the various LT1 markers.

Case 3 (8/17/21):

Data from a blog reader consisting of Fatmaxxer output (Polar H10), artifacts unknown.

Ramp 1:


Ramp 2:


  • Although HRVT power and HR are not exactly the same, they are within reasonable limits. 
  • The question arises whether the ramps are comparable since one was after a recovery ride, which could have introduced fatigue effects.
  • Another session of two ramps done back to back did not have a good linear a1 drop.  Reasons are unclear and I did not have the raw data to delve into why.

Steady state power/HR sessions done below the HRVT
 
What we are looking for is a grouping of DFA a1 generally above .75 (with occasional dips) during a session with HR below the HRVT (142-150):


Session 2


  • This is an excellent example of a true recovery session where the majority of a1 values are above .75 along with a HR in the appropriate range.
  • It also illustrates that the distribution of a1 can be wider than you imagine, despite a steady state power/HR.



Heart rate variability during dynamic exercise

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