Automating Recovery Analysis for Sleep and Exercise Data
There is a history option which allows one to review the last week of data collected one screen at a time. I have been slowly increasing the environmental stressors around my training. More weights, faster swims, runs in high summer temperatures and sleeping at elevation. I’m starting to see the gains with my recent rMSSD peaking at 68 which is 13 ms over my baseline for this three week period.
The baseline view provides the same data in terms of “Recovery Points” (higher is better), “Heart rate” (lower is better) and rMSSD (aka HRV – higher is better). You want to see the dark blue line climbing on the Recovery Points and rMSSD and dropping for Heart rate to know that you are progressing in a positive direction. An hard training session will briefly skew the data, but the point of baseline is to see overall progress and not get hung up on a single event.
The population view is one of my favorites as it shows where I stand compared to others my age and gender. This is a helpful metric to set realistic goals around. It is also fascinating to see the outliers. An example of a goal to set is to boost rMSSD from 55.4 ms (my average for the last month) to This feature of comparing oneself to others based 70 ms next month. This might require not drinking alcohol, going to bed an hour earlier each night and bringing in an extra high intensity interval training session each week.
Finally, there are some really cool insights. Most of these require a minimum of 30 – 60 days of data collected. These tools provide just what an active person needs to understand how much they can push themselves and still be optimizing performance.
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