Monthly Archives: May 2014

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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Base Rate for HRV Recovery Study

I am now looking at my recovery time from Upset Reactions and am focusing on Self Induced reactions while sitting working at a computer. I chose this category because it was the source of a high number of reactions in my Intensity Study and I can control the environment with respect to food, water, sleep and logging. I explain Self Induced vs Direct reactions in an earlier post. For simplicity, I am looking at two states of being and the time spent in each.

The first state I will call Upset. This indicates either anger, anxiety or some sort of mindful distraction that is sometimes indicated by a low Heart Rate Variability (HRV). Heartmath calls this being out of coherence.  The second state I will call Poised. This is a state of relaxation, mindful attention and calmness. Its quite pleasant and conducive to connection with others and creative thought. The general idea is I want to be Poised more than I am Upset.

Upset recovery time means the number of seconds from when I move into an Upset state  as read by the Heartmath Pro software to the point when I once again return to a Poised state. These periods of Upset can go from 5 seconds to 5 minutes when I observed them.

I established a baseline by measuring my movement from a Poised state to an Upset state over a period of five one hour sessions.  The data:



With no intervention at all 20% of the Upset periods were over 60 seconds in length. 36% of the Upset periods were over 30 seconds in length. Looking at those in terms of total seconds it was 41% of the Upset time was batched into the combined periods that were longer than 60 seconds. Those Upset periods that were over 30 seconds accounted for 60% of the total Upset time.

Looking at all Upset periods combined, 27% of the time I was sitting working on my computer I was not in a Poised state. That means some bit of information I was seeing on the screen triggered an Upset reaction. There really is no reason for that as I was comfortable in a situation that had no immediate danger.

If hypothetically I could train myself to ensure my recovery from an Upset reaction was less than 30 seconds due to some intervention on my part I could have in that same period added back over 67 minutes of Poised time. Given the baseline period was five hours that is a large number and if my intent is to be more Poised then Upset, certainly worth the time to explore it.

Next I am going to use Taplog and the Heartmath Pro in tandem to determine if the act of logging an Upset changes recovery time.

Why All This About Stress

Somebody asked me recently why I was doing all this work on stress. Was I that stressed out? The answer is actually the opposite. I currently have a very low level of stress. A few days ago I was giving a presentation to an organization and left the office without my power cord. It was a long way to go back and I had other things to do. As I began calmly solving for the problem I noted that I can remember how similar situations in the past would have sent me apoplectic with rage at my stupidity for not being organized. Now I just solved the problem with a fairly calm demeanor.

Three years ago I noticed that I was experiencing the same level of anger and anxiety that I can remember having when I was much younger. Life has turned out pretty well for me. I have a great relationship, some trophies on the shelf and a lot of good fortune. Surely my stress should be dropping as with time there was a lot less to be stressed about. It wasn’t the case.

Always being interested in mastery and learning I wondered if stress reduction could go beyond learning some basic cognitive behavioral therapy and doing yoga. Could I actually master stress reduction? So I started to look into it and tried some techniques. And it is a funny thing about Quantified Self. Once you have a little data getting more is always more appealing. So I study stress because I am a lot less stressed and I am more intrigued the more I learn.

Real Time HRV

I have now moved to monitoring and playing with Heart Rate Variability and have to say even early experiences have been really fruitful. I played with Zensorium’s Tinke which I liked for ease of use. I also have the iThlete heart rate band which as a former triathlon participant I really appreciate. I also got the Heartmath product, both Pro and Ermwave2. I use the Android Paced Breathing app which is simple and easy to use throughout the day. And I log everything on Taplog because though all these useful tools will tell me my HRV, only Taplog lets me log what is going through my mind at the different reading points. In the mix is the powerful monitoring.

Here is a 10 minute session using Heartmath this morning:


I used their “coherence coach” and was staring at a nice screen hearing soft music and an image of a ball that went up and down the entire time. How I felt at the end of that 10 minutes was remarkable. The circumstances included a quiet room, me focussing on my breathing and birds chirping outside. Pretty much ideal.

However, life it not ideal. So the question I have is how to reach this state of coherence as I go through life between pillar and post. The marketing materials say that doing that 10 minutes a day in that state will have a dramatic effect on the remaining 1430 minutes. Mathematically that seems odd. However, that is why we are here. To test and learn.

Intensity Study Wrapup

The Intensity Study was based on 242 logged events over 24 days looking at multiple factors that could effect the intensity of my upset reactions. In four previous blog posts I have shared the details of Direct vs. Self Induced triggers, Past vs. Future triggers, Movement vs. Stillness, and various environmental factors like water intake.  Here are some summarised thoughts of what I think I saw in the data:

1. The standard unit of a day may be too long for meaningful correlations. Averaging noticed intensity over the day did not yield much against other factors like sleep and activity. I don’t think this proves or disproves anything. It just means that the day as a period of measure is inconclusive in the type of work I am doing.

2. Dreaming up future mini-disaster scenarios is the brain’s specialty and the numbers show it is a rich source of the stress triggers I experienced. If I am going to create some hacks to short circuit stress triggers, I will start with defusing the constant thought stream of future bad outcomes.

3. Movement and stillness consistently delivers a different experience of the stress triggers. When moving there is something in navigation and solving for the locomotion of oneself that pushes aside more distant concerns. Seems obvious, and there are some hacks that I am already considering using that dynamic.

4. Conscious self reporting has its limits. As of 8am this morning I have logged over 3,361 incidents where I noticed myself being angry or anxious. The first logged entry was on 7 Sept 2012. I think as a practitioner of this particular form of logging I can be considered experienced. Yet work with Heart Rate Variability (HRV) monitors show me that I miss a large number of moments when my physiology is showing a stress reaction, and when I stop and notice there is indeed some thought bubbling around down there.

My next study will be with the aid of HRV monitors to see if the tactical triggering of physiological stress brings us to the same conclusions around future scenarios and movement.




More Water Please

Looking for correlations with factors that effect the intensity of the upset reactions over the course of a day I compared the average intensity of different stress states for the day with the following factors:

  • Sleep the night prior
  • Water intake on the day
  • Coffee intake on the day
  • Number of minutes of Paced Breathing work
  • Minutes very active (walking/cardio)
  • How hydrated I was on average over the course of the day

Across these factors I looked at the average daily intensity for:

  • All upsets
  • Direct upsets where the trigger was in the immediate environment when logged
  • Self Induced upsets where the cause was not in the immediate environment
  • Self Induced upsets when Standing
  • Self Induced upsets when Sitting

The was only one strong negative correlation (r=-.43) and that was Water consumption and Self Induced upsets. Coffee intake had a moderate negative correlation (r=-34) on Self Induced and minutes very active had a moderate negative correlation to Self Induced while Sitting (r=-.33). My actual state of hydration had no correlation to upset intensity.

Of interest was that none of these factors had any significant correlation to the intensity of Direct upsets. Water had a weak correlation (r=-.24) to Direct and every other factor was not correlated at all. Direct upsets seem to have an intensity that is related to the environmental factors.

So adding to our other insights we see that controllable factor of water & coffee consumption can help with the category that has the highest intensity & number combination, Self Induced upsets. So it seems that drinking some water and taking a walk might be efficient ways to reduce thinking about future disaster scenrios. But of course, that remains to be tested.


Intensity Study – Stillness & Movement

One of the new dimensions I wanted to look at with respect to Direct and Self Induced upsets that I describe in my first post on this study is my physical state when I logged the upset. So using Taplog I created category buttons for lying, sitting, standing and walking and captured those states when I logged the upset. Over the period here are the volumes of triggers based on these states:



Sitting and standing are the states that predominate my entries. I noticed qualitatively that when I started walking the simple problem of navigation arose to displace a lot of rumination. This bore out in the numbers. Here is the breakdown of Direct and Self Induced by physical state:



Standing and sitting both had an almost equal number of Self Induced upsets. It looked like my mind would wander when being physically still. The types of Direct upsets that arose when sitting were encroachments of space, usually while travelling. Looking at the average intensity by physical state showed that standing upsets were more intense than sitting:



So comparing the future and past orientation of upsets I reported yesterday with this data would show that the largest category of stress if I combine number, type and intensity would be standing and ruminating about some disaster scenario that I think may occur some days hence. So if I were to prioritise remedies the easiest would be to notice when I am standing and thinking about some future event to breathe deeply and start walking.


Intensity Study – Past vs. Future

I was interested in where my mind goes when something occupies it enough to cause an upset. Earlier studies showed that I had a Direct trigger, meaning something was in my environment causing the thought, and a Self Induced trigger, meaning I was thinking about some other circumstance outside of my immediate environment. The trigger in that case was indirect and beneath my conscious awareness. I wanted to see if there was a difference in whether I was thinking about a future event (anticipation) or some past event (memory) in the Direct and Self Induced triggers. Here is what I found for Direct triggers.



The split between past or future was close to 60/40 with more of my upsets being something that had just happened in that moment. For example, when a man on a plane kicked me and I became irritated I was operating from an immediate memory. When I walked up to the visa window in Cambodia without the right currency I saw the window and was anticipating a problem getting the visa in the moment that was to come.  When I looked at the Self Induced triggers an entirely different picture emerged.


When there was no Direct trigger in the environment the thoughts were predominantly of the future and the time horizon was mostly beyond the current day.  Of the 24 thoughts about the past and qualified as Self Induced, only 4 were prior to the current day. The other 20 were very recent (same day) and the only reason they were not Direct is that the source of the trigger was no longer near me.

As a percentage of the whole, Self Induced Upsets regarding some far of future event represent 52.7% of the triggered upsets. Second in order of volume was Direct past at 21%. Generally the answer to the question of where my mind goes when it is occupied is either some distant future disaster scenario or a recently remembered irritation.

I will address specific strategies to reduce upsets overall in future posts. The data shows that creating a program where reducing future facing Self Induced upsets and instinctively letting go of Direct upsets as they happen can relax 73.7% of the triggered upset events. By watching that data a Personal Performance Design starts to emerge.


Intensity Study – Direct vs. Self Induced

With 242 logged events over 24 days I have some initial results of the current intensity study. I always break the upset events into two categories, Direct and Self Induced. In this study I logged more specifically whether the source of the upset was in the immediate environment. The rule was that I would call it Direct if I could physically see the source. If the source of the upset was not visible I logged it as Self Induced. The result:



If you recall in the first study I found 75% of the upsets were Self Induced. The second study showed 65%. In the first study I had seen the number of Self Induced upsets drop as I observed them. The second study’s lower % may be from training myself in the first study. The trend continued in this study of showing a lower percent, though even with training and focus 60%+ of upsets are Self Induced. I can say qualitatively I am dreaming up fewer disaster scenarios.

Tomorrow I will share breakdowns of intensity based on the physical state of lying, sitting, standing or walking.