Tag Archives: performance interaction

DIY Tracking the Daily Energy Curve

I have reported in earlier posts that I am mapping my Daily Energy Curve so I can make changes in diet, exercise and mental frameworks that will maximize my physically feeling good. In the world of self quantifying we tend to maximize for a desired weight, blood glucose level, steps we take in a day or distance we can run. It gives us an organizing principle for our activity and measurements. My current work is to maximize just like this guy does:

feeling good

I needed a simple way to capture how I was feeling at different times. I like Taplog but it is only for Android and I had just switched to iPhone. I could not find an iPhone app that I liked. So I created a Google Form that would be easily accessible on the iPhone and I could capture my data often.  The survey on the phone looks like this:


I started gathering reports along three dimensions, six times a day. The dimensions were how awake I felt, how mentally sharp I felt and how stressed I felt.

I am very early days so I can’t describe what I have learned yet. I can show you what the early data looks like and how much data you can gather with a DIY tool like the one I created. This represents four days of data and 37 data points.

Here is the early data on how Awake I felt over the course of the day:


I was surprised to see how much the curve held up in the back end of the day. Here is mental alertness:

Mental Alert

Too early to be definitive but the drop the afternoon seems to be interesting.  The curve for how stressed I felt has a different and flatter curve:


I can now start running randomized experiments on the day parts. I am pleased to have created this tracker because I have a lot of control over what I can capture and I already have expansion ideas. And it keeps my tracking top of mind.

I encourage you to make your own DIY tracker. To help you out I have created a set of step-by-step instructions in a PDF and you can download it for free on QuantXLaFont.

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Fort-Six Meditations

I was pulling data yesterday preparing my speech for the Quantified Self Conference & Expo. I have been collecting heart rate variability (HRV) readings since October during conversations with work colleagues. My hypothesis was that I could train myself to be like a conversational ninja and outwit people using my physiology.


I had to ensure I could bring myself to a relaxed state by practicing sitting in a meditative state each morning for five minutes. l talk about the value of this in my tutorial post “By Yourself – Basic Training.”  I wanted to train myself to get to calm in five minutes or less.

For these sessions, I use Heartmath emWave pro because it has a very clear interface. It uses an ear clip that ties to software on my laptop and this is the dashboard I see during the session:


I can see my HRV wave on the top part of the screen and get a score on how I am doing on the bottom. I don’t recommend the emWave pro based on its high price. You can use a phone-based app for the same five-minute session. But I have one so I use it.

In prepping the speech, I pulled the data on 46 meditative sessions to see if I was getting fight/flight readings when I was purposely downshifting my physiology. These sessions were spread out over multiple months and consisted of 17,872 heart beats. I analyzed these beats looking for fight/flight incidents using a technique I outline in my HRV Tutorial. The number of fight/flight incidents?


That’s right, zero. Over all of those sessions, I did not have a single incident of extended fight/flight during those sessions. So I had in my Basic Training learned how to bring myself to a relaxed and refreshed state very consistently.

I’ll be talking how I wove this training into my conversational experiences as part of my speech for the conference. I’ll also be rehearsing this speech this Wednesday at the first Denver Quantified Self Meetup. If you are in the area stop on by.

My Quantified Self 2014 in Review

I had a good Quantified Self year this year. As a long time logger and casual athlete I have always logged my personal data in some form. This year with the support of the Quantified Self community I was able to explore two specific areas. First, I moved stress tracking from self reporting to the use of wearable devices. Though I bought a few more devices than I would have liked I found that heart rate variability measurements using $65 worth of equipment was sufficient to track stress. Second, I was able to pull out insights about consciousness and heart rate variability that set the stage for future studies.

I explored 20 ideas this year that I organized into five umbrella studies. I started looking at the data I had collected through self reporting of “Upset Events.” I followed that up with a look at Upset intensity given different situations. After seeing the limits of self reporting I started using different devices to measure stress, settling on Heartmath used during working session. Using the device I discovered Freakback can have an effect on results. After learning how to work through that I completed a first study on how I recovered from Upsets.

As I was conducting these studies I had an emerging idea that emotion is navigation. The regularity of emotional shifts seemed like “sighting” as I worked through different ideas. As I worked on this idea I found that Heartmath was too limited in what it measures. Heart Rate Variability has a more direct measurement in rMSSD. I dropped Heartmath and started using Sweetwater HRV’s SweetbeatLife to monitor rMSSD. Using this tool I started measuring stressful events like getting a tooth drilled and firing a shotgun. I played with machine learning and straight statistical regression and determined my “stress point” when read by rMSSD. This provides me a tool to study a variety of situations going forward.

Along the way I gave five Quantied Self meetup talks, 2 in London, 1 in Amsterdam and 2 in the Bay Area. In London and Amsterdam I did my talk We Never Fight on Wednesdays, and in London my followup Don’t Just Stand There. In the Bay Area I presented my talk Every Other Minute where I talked about the navigation impulse. And finally my Bay Area presentation on heart rate variability and Flow. These talks went well and I am set up to give a presentation at the QS Global conference (QS15) in June.

Some of the 20 ideas did not pan out. My work on 800 numbers went nowhere. Ideas about reading my heart rate while doing The Work by Byron Katie did not have sufficient detail to be interesting. Several other ideas blew up on the launchpad. However, I’m pleased with the progress this year. In my next post I will talk about the lessons I have learned during this work.

Measuring When With Others

Pretty big design problem to solve is how to collect real time information when sitting with others. When by myself I can record my thoughts by speaking them or logging them when I see the device flashing red. As I described in my post on the respiration study I had a pretty clear system to recover when I was flashed into the Upset state. Yesterday I described how I want to take this work to understanding the Upset vs Poised state when in communication with others. Hard go.

I measured two interactions yesterday, one using Heartmath and the the other using SweetbeatLife. When I did the first interaction I was able to record it as it was by phone, but I was Freakbacking like crazy. I was on a call with the bank and watching the Heartmath monitor and as it flashed red I was trying to correct for it which made the situation even worse. As I was trying to talk to the woman on the phone the reading went haywire and I ended up actually going into a very high state of stress. It was a case of way too many inputs. When I listened to the recording I could hear the stress in my voice. Freakback central!

The second interaction was with a good friend over coffee who is sympathetic to the cause (and who is going to read this) and I just had the SweetbeatLife on monitoring my heart rate and HRV. We talked about a variety of things to include drones, dystopias, quantified self and monitoring oneself when talking to others. At the end I showed him that I was monitoring my own HRV during the discussion and he appropriately asked if I had recorded him, which I hadn’t. And what I got was a contextless HRV and stress line that in no way was helpful because I did not know what was being said or what I was thinking as the line moved during the discussion.

So in both measured interactions where i was looking for ways to be more engaged with people I either reduced engagement by Freakbacking or got a measurement that really was not useful even in review because I could not tag it with what was happening in that moment. Somehow I need to hack together a way to capture thoughts unobtrusively while not violating the privacy of others and transparency in connecting because somehow them knowing they are being recorded or my knowing that I am not being transparent in the measurement would cloud the connection.

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.