When I started looking at Heart Rate Variability (HRV) as a tool to train myself I was drawing on my experience using heart rate monitors for physical training. When I went for a run I would see my heart rate in real time and adjust my exertion accordingly. I found this a powerful way to both increase my fitness and extend my training by not overdoing it.
Most of the apps today either lack context on the data they gather or give you a passive report on a past period of time. For example, the Jawbone UP tells you your steps but it is up to you to index that against other measures to see if you are improving your fitness. Multiple HRV apps will give you a coherence or stress reading after a session is complete. Two apps I am using now structure the feedback in ways that make the experience more interactive and provide good enough context for a user to take action in real time.
Stayfit by Marco Altini. I have just started using this app and really like it. It does not use HRV, but it creates very nice context by indexing resting heart rate against daily exertion. A quick measure of resting heart rate in the morning is very easy to do, then watching your exertion the rest of the day helps you work on fitness. The interface is very clean:
I find that I look at it often during the day to watch my kilocalories expended and make adjustments to my schedule and activities to increase exertion for the day. It is only available on iOS is its only drawback.
Breathe Sync by Michael Townsend Williams. I have written about this app in an earlier post and still have it as one of my go to apps. The reason is that its primary use case is to bring you back to a coherent and relaxed state very simply and quickly. It does give a measurment but that is a secondary part of the experience. The camera on your phone picks up your heart beats and then shows with a simple blue and white ring visual how your heart rate is slowing or speeding up as you see here:
Over the course of the session the ring visual will allow you to match your breath with the increase and decrease of the interval between heart beats. Very powerful and effective. I use it when I feel amped up or just prior to a meeting to get into a balanced place.
The context of indexing one measure against another in Stayfit and the very active intervention quality in Breathe Sync put them both on my daily use list. Ultimately I want to train myself to use awareness and respiration to set myself “in the zone” when it comes time to negotiate, interview and brainstorm in a professional setting. These two apps are great tools as I work on getting there.
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.
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.