Monthly Archives: May 2014

Breaths Per Minute

I purchased a Tinke at the QSEU14 conference and have used it to start to collecting data on respiration and HRV. I am still at the peak of collecting for my physical movement versus reaction intensity study but as a collector I can’t help myself. I have noticed a couple of things in the collection of the data. First, my Breaths Per Minute when I take my measurements are double the rate at twelve that the science tells us is the “downshift” rate where you go from fight/flight to pause/plan which is six. So my breath rate when I am sitting in a chair during the day thinking I am relaxed is potentially keeping me nearer fight/flight. Also, I am seeing a pretty consistent HRV measurement during the day despite perceiving that I am relaxed or upset. It looks like the feeling of upset is not consistent with what is going on in realm of physical response. Rich veins for future studies.

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Day Part Platform

The problem to solve for a Quantified Self study to be meaningful is how difficult it is to isolate a single variable enough to ensure your data is useful. For example, if I want to see the effect of smelling peppermint each morning on my waking and I am not sleeping the same amount each night the effect of peppermint will be lost in the context of shifting sleep amounts. I may be more or less awake based on the quality and volume of my sleep which has nothing to do with peppermint.

A potential answer to this is to create a habitual Day Part Platform that constitutes some stability in the underlying factors of physical experience on top of which the Quantified Self scientist can then vary factors and measure the effect. To be effective, the Day Part Platform will be based on habits built over time. The good news is that the science tells us that routine and rythmn is positive for health,so building a measurement platform will also benefit with more stable moods, sleep and experience.

Here is how my Day Part Platform. A day qualifies as “stable” if I:

  • have 7.5+ hours actual sleep as measured by Fitbit Flex
  • do 30 minutes of cardio before 10am
  • stretch doing a 12 exercise active stretching routine after the cardio
  • drink at least 2000 ml of water
  • eat in the range of 2200 to 3000 calories

At the end of each day I determine if that day qualifies as stable and can be included in the study. If I have flown or had a big meal out with friends, etc, I simply exclude that day’s data. As my main area of interest right now it being able to consciously shift from fight/flight to more relaxed and productive states I think the day construct is useful. And because this is work with the Quantified Self I will play with it and see if it needs modifying with experience.

Quantified Self EU Conference

Just back from the Quantified Self Europe 14 conference in Amsterdam. Fantastic people and a wealth of ideas. I learned a lot, and came away with much to consider. Quantified Self is still in early days as the frameworks are very personal and the topics range from muscle tension to Parkinson’s Disease. What is common is the impulse to understand the self, and the impulse looks and feels like a gathering of data scientists, but the flow is one that is almost spiritual.

At its core the seeming desire to show ones data to others is really the impulse to use one’s data to create a narrative. The conference was a storytelling session rich in ideas and individual tone. A remarkable experience. I gave a talk on Upset Reactions and it nicely brought to a close the 18 months of work I have done on the topic. I now will branch out and build on the work.

Fixing Sleep Data on Fitbit

When using Fitbit it is quite easy to forget to tap in for a nights sleep. Fortunately the Fitbit still captures your movement and you can log in the hours based on what you see. The method:

1. Go to your Fitbit home page and log in

2. Go to “Log” and the sub page “Sleep.” This is where you can update your sleep log.

3. Create a new sleep record approximating the hours you think you slept. I usually start it an hour before it think i went to be and put the waking the hour after I think I woke up.

4. Look at the resulting graphic. It will show when you were moving and when you were inert. It looks like this:


5. You can see where there is a concentration of red movement. On the graphic above you can see that I started getting really active at 7.30am. It s probably I woke up at around 7.45am, not 11am.

6. Edit the time as appropriate


7. You now have a more accurate representation of your sleep cycle.


Capturing Thoughts

In an a blog post about resetting out mental inbox to zero, the author cites the statistic that researchers thing we have 50,000 thoughts go through out heads each day. In my experience I log from 5 to 25 thoughts per day when they come to my attention as negative or distracting. That means on a good day I am capturing .05% of the thoughts I am actually having.

So what is the purpose of logging thoughts? It cannot be to capture the overall population of thoughts and deal with them one by one. Simple math says we are having a thought every 1.8 seconds. The purpose of logging and meditation is positive in my experience, but the skill set I am building is absolutely not to capture and dispose of all thoughts.

What must be happening is the underlying context and connecting beliefs beneath the thoughts shifts from “these are 50,000 representations of reality that must be true” to “these are 50,000 impressions that may or may not be true.” That small shift allows an arising thought to be seen in context as one impression in a stream of impressions.

An analogy could be this. Each message in your email inbox is an electronic message that may or may not be important. Some are critical, most are irrelevant. We have learned with time to scan for the important and ignore or filter the junk. So too with thoughts. Instinctively we can shift to where thoughts have no credibility just because they are thoughts. Some will help us look both ways before crossing a street. Others such as self criticism or fear of the unknown we let pass to the junk folder.

So a Quantified Self strategy is to log thoughts that correspond with feeling, and see that in your sample set of 5 to 25 some are important and most are riddled with error. With time and practice you will not look to get your email box to zero…you will enjoy knowing that you are good at filtering the good from the bad. And knowing how to do that will bring you peace.

Paced Breathing & Upset Intensity

Using a small set of data from my ongoing study I am seeing a negligible correlation (r= -.1) between doing fifteen minutes of relaxed paced breathing and the average intensity of upsets for that day. So meditating in the morning doesn’t fix you for the day. I had this small theory that came from my own imagination that a session in the morning would help me on that day. Data doesn’t show it.

I am going to keep looking at this across a larger set of data and a longer period of time because meditation is widely reported having positive effects. On the scale of  a single day there is no mantra driven cure for how your stress reactions in the world.

Physical Movement Effect on Upset Reactions

If you have been following my work on upset reactions you will know that I have identified two types of upset reactions. The first is Direct, ie when a car almost hits me. The second is Self Induced, ie when nothing in the immediate environment is happening but my mind wanders to some disaster scenario that may occur in the future.

I set up the analysis sheet today so I could export data from Taplog and fitbit premium and start playing with some of the early data. The full study will look at the intensity of Direct and Self Induced as it correlates with exercise, paced breathing (meditation), water consumption, and coffee consumption. I will not comment on those results because I do not have enough data yet.

I have also been collecting the physical action I am taking at the time of the reaction be it lying down, sitting, standing or walking. When I register a reaction I use a 1 – 9 scale, 1 being just the whisper of a thought, 5 being an body feeling and 9 being full on rage or panic. Here is a very early teaser on the intensity difference relative to physical activity.


Early data on lying down looks like I only have Self Induced stress which makes sense as this occurs near sleep. When I do this the average is sub-physical sensation and the population standard deviation is lower than 1. I think this means I catalogue concerns like schedule for the upcoming day and the intensity is fairly standard.

When sitting the average intensity was sub-physical and close together with population standard deviations close to each other but greater than 1. i think this means when I notice things in the environment, be it a screaming child on the plane or a to do pops into my head that I react similarly within a range that is consistent.

When standing I have an average upset intensity for both Direct and Self Induced that is experienced at the physical level.  When I look at the notes from the reactions I see many of them derive from events that are in motion – waiting for a taxi or talking to someone. Interestingly, even the self induced reactions average higher when standing than when sitting though the population standard deviation is the exact same. So something about standing seems to put me in a more intense frame of reference.

Walking shows the highest average, well above physical, for Direct. This makes sense as walking is where more “car almost hit” incidents occur. Navigations creates upset reactions. The world is dynamic and the mind is on alert. Self Induced reactions, however, are sub-physical when walking and the topics are very similar to when I am sitting or standing.

So the results make sense at a summary level. The more I am moving the higher the average intensity of Direct reactions due probably to navigation. When I react to a Self Induced topic while standing I have a higher average response with a larger range of feelings than in other states even though the topics are similar.

This data indicates a potential corrective course of action. Most Self Induced topics are similar whether I am lying down, sitting, standing or walking.  So if I am standing and feeling mindful about some future disaster scenario, a potential correction is to start walking. If that is not possible, I need to take a seat!