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.
Taking a baseline reading with Heartmath Pro in the busy and noisy airport.
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.
Ran across this study done by Kira Newman. She tracked her moods for a month using an alarm each hour. In her report there are comparisons, correlations and good insights. I commend Kira for the work she has done which has great detail. Her insight that her stories effect her happiness is an important one.
When it comes to the “science” of Quantified Self we should continue to improve our rigor, and we should not be afraid to try new things. I found myself very rusty on statistics and had to go back to the basics just to understand how to get a correlation out of an excel spreadsheet. It was painful, and after some hours on Khan Academy I got myself back in the game a bit. And I am having a lot of fun.
Thanks for the inspiration Kira and on we go!
A nice article on why Nike shut down its Fuelband effort that calls the move “an indictment” on wrist wearables. I think the indictment is on a magic bullet that device manufacturers are keen to create, market and dominate with sales. In the article there is the statement that Apple will come out with the ultimate device, but it is not likely that they will create the magic bullet either.
This blog is about Quantified Self and experiments that can be done with a variety of devices and methods. What is hardest is thinking of the desired outcome and designing the activity. The tracking is easy. Tracking devices are abundant, methods to set goals and design activity are hard to find.
Real life changing effect of wearables will come from accepted methods of combining data with activity. And this space of “try this and watch” is the true open space in the Quantified Self arena.
Brushing up on my statistics I was reminded of the difference between a sample survey and an experiment. When the laboratory, population and subject of your efforts is yourself it is difficult to have a control group. You can’t have a double blind experiment when you are the experimenter and the target of the experiment. Even gathering information can be difficult as self reporting is entirely subjective. Here are three things I have found:
Surprise yourself – Design data collection in a way that a silent alarm triggers you to enter some information. Your conscious mind will forget that you are studying yourself and you will get a truer measure. For example, when I entered information about my mood based on when my mood was bad I would enter it inconsistently. When I set a silent alarm and entered my mood every time it alerted me I got a much nicer survey result.
Use Devices – Devices on their own can be a distraction if they are acquired for their own sake. When quietly observing your activities and collecting on an ongoing basis as part of a study you are conducting they are excellent. The data collected can be surprising and useful. And use your devices to support your studies. Don’t buy them for their own sake.
Keep Study Period Short – A fourteen day study can give you a good sample set. I have let my studies go for a very long time and though I had a mountain of data at the end, the insights could have come in shorter periods. Shorter periods keep you moving through topics quickly and can prevent exhaustion.
Quantified Self studies are in early days. We have a lot to learn, and a lot we need to discover. Keep surprise and time on your side.