The Effect of Logging on the Return to Poise

In my post on Base Rate for HRV Recovery I outline the details of the Poised state versus the Upset state. What I am measuring is the effect of active remedies taken when the Upset occurs. The environment was working on the computer with as many variables as possible (sleep, exercise, food, etc) unchanged. I had the baseline data as described in the earlier post.

For the first test I wanted to see the effect on the amount of time it would take to return from Upset to Poise by simply and consciously logging the Upset. I used the Heartmath EmwavePro, Taplog and an Olympus VN-733PC digital recorder. I set the EmwavePro to make a low sound only when I my Heart Rate Variability (HRV) indicated I was in an Upset state. When I heard that, I would log the time on Taplog and speak what was on my mind into the Olympus recorder. At the end of each session I was then able to assemble a spreadsheet showing the Upset time, the length of time I was in the Upset and what I was thinking that may have triggered the Upset.

Over five hours of logging I had a list of 169 Upset events. Of those, 19 were about the process of doing the observations itself, like getting the devices to work. So 150 environmental triggers created upsets. In the baseline study the number was 124. So a generalization can be that while working on the computer some stimulus sends me from Poise to Upset every two minutes.

Each Upset had a different recovery time, which I have displayed in this chart showing the number of upsets by length of recovery time. I show both baseline and logging results.



Of interest is that there were an equal number of “long trigger” (over 61 seconds) Upset events and a large difference in the under 15 second group. There were nearly twice as many under 15 second events when logging than when doing nothing (baseline). I noticed that interruptions in attention cause short Upset spikes, and the act of logging was full of interrupted attention. Was that interruption worth it? Only if the total number of minutes in Upset was reduced. Here is the chart showing total number of minutes grouped by length of time.


This picture is much different. The similarity is on the low end of the scale, meaning even though there were double the number of Upset events while logging, the amount of time not Poised was not nearly as impactful on total time. When we get to those Upset events that were 46 seconds or over, the baseline number of seconds in Upset state are clearly higher though the number of triggers were similar.

So it does appear that logging tactically reduces the amount of time spend in Upset. How much? The total time in the 5 hours of baseline readings that were in Upset was 27.6% of the time (82 minutes out of 300). The total time in Upset for Logging was 26% of the time (78 minutes out of 300). So logging “saved” about 4.6 minutes out of the 300 total. Not an impressive result if we expect to have an active measure deliver us back more time in the Poised state.

Next I will be measuring what the literature considers the largest lever we have – respiration.

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