Proposal - Heart Rate Recovery Metric for Interval Workouts

[Coach_Ron]

One for @david :

In interval workouts, I’ve always checked how quickly my heart rate falls before getting on with the next bout.

In activities with heart rate data and recognizing interval format, how hard would it be to scan for heart rate recovery and report that as a min, max, and average of all intervals?

To make it simple and applicable to all interval formats with different recovery intervals, the heart rate recovery could be simply computed as difference from previous peak HR to the value it achives in the subsequent 30 seconds.

Heart Rate Recovery_30s = (Peak HR - HR after 30 seconds)

So it would be a beats/30 seconds scheme. If someone wanted to know what it is for 1 minute, they could just double the value.

It’d also be interesting for athlete to compare this metric for intervals of similar structure. The value would be to assess if the recovery has been good, if a sympathetic & parasympathetic balance exists and to put this metric within context of all the other stressors in the life of athlete at that moment.

Thoughts?

Thanks,

-Ron

Ron George

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[Luisma_Gallego_Soy_P]

To assess sympathetic-parasympathetic balance we are using rra1 and dfa-alpha-1 values, and so far the results are quite good.

[Coach_Ron]

Sure. I’m suggesting a more easier method.

How are you assessing dfa-a1? Are you using the Garmin app? Please describe your workflow if you don’t mind.

[MedTechCD]

@Coach_Ron Luisma is one of the driving forces of that Garmin app. Inigo is the dev.

[david]

You can do that using a custom interval field and some Javascript:

{
  let hr = streams.heartrate
  let peak = hr[interval.end_index - 1]
  let after30s = hr[interval.end_index + 29]
  //console.log("peak", peak)
  //console.log("after30s", after30s)
  let recovery = peak - after30s
  recovery
}

I have published this one so you can search for it. It is under “Antoinette” because I tested it on my wife’s data. She has been doing 4x4 VO2 max on the trainer recently.

It assumes that the last point of the interval will be the highest HR and that the data has 1 second per tick.