Ten Things I Learned at the 2014 Quantified Self Europe Conference

QuantifiedSelf Europe 2014On May 10th-11th 2014 I had the pleasure of attending (and speaking) at the 2014 Quantified Self Europe conference in Amsterdam. I have attended the annual US conferences the past few years, so I was excited to see lots of familiar faces, and even more new ones. It was a fun, educational, and inspiring time and my post-event buzz still hasn’t worn off (whereas thankfully the Jenever has!).

In the spirit of Quantified Self’s “Show and Tell” talks, I’ve structured my recap using the 3 questions every presenter is required to answer…

What Did I Do?
I attended Quantified Self Europe 2014.

How Did I Do It?
I registered for the conference, prepared my talk, and eagerly got on a plane from New York City to Amsterdam, where I took a short train ride to get to Hotel Casa 400.

What Did I Learn?

1. So many great sessions (and not enough time!)

The conference was so packed full of great talks and breakout sessions happening at the same time that there was simply no way to see it all. Fortunately, most of the talks (including mine!) were recorded and the QS folks will be posting videos shortly. I often found myself running from room to room to take in as much as possible or walking in late because of a great conversation I was having during one of the breaks!

Quantified Self Europe 2014 Breakout

credit: @addappio

2. Privacy concerns shifting from “mine” to “yours”.

Whereas the QS privacy/data debate has focused on the self, there was a much more awareness about factoring in the privacy of others we may be recording without their consent/knowledge with the proliferation of “lifelogging” devices. And even with all of this lifelogging going on, ironically, not one person posted a photo of me giving my talk on the conference Flickr stream! (please send me a pic if you took one :))

Narrative Clip

credit: Jim Tuttle/NPR

3. Europeans have a much better fashion sense than Americans.

Amazingly, I did not see one person wearing a pair of Vibram Five Fingers. Sorry San Francisco!

QS-shoes

credit: Rajiv Mehta

4. QS is not just about health.

While much of the QS subject matter has a heavy focus on health/wellness, people are using self-tracking to better understand all aspects of their lives, from productivity to grief, improving memory to goal setting, improving relationships to tracking media consumption, to even transforming data into art!

Quantified Self Data as Art

credit: @kiranezu

5. But as it relates to health, QS…

Is evolving from people sharing stories about identifying/treating/overcoming existing problems to using self-tracking as a way to take proactive/preventative measures to ensure they can live optimally both today and in the future (what’s the point of living a long life if you aren’t able to truly “live”?).

Quantified Self Europe 2014 Fitness

credit: @yago1

6. Quantified Self vs. Biohacking

While QS and biohacking are very connected, not all QSers are biohackers, and not all biohackers consider themselves QS practitioners. This seems to be becoming more evident as practitioners begin to push the envelop on both fronts. I personally view myself as someone that falls smack in the middle – an avid practitioner of both.

Quantified Self vs. Biohacking

7. QS is a global movement.

Probably my favorite part of the conference was that as an American, I was of the minority in attendance, and it was great to engage with so many people from other parts of the world. They really brought a fresh perspective to the QS conversation. That being said, as much as I love San Francisco, I think future QS conferences would benefit from moving to locations outside of the San Francisco/Bay area, where it can feel very insular and disconnected at times.

8. Startups, startups, startups.

As the QS movement continues to grow, so too is the QS-related startup ecosystem. It was great to see companies that just a year or two ago were nothing more than a prototype finally launching and raising some serious capital. In addition, some big established companies are beginning to show up (from consumer electronics to pharma). I hope that future conferences can maintain their content focus on allowing individuals to give talks about their personal journeys and not having the talks get too commercial/salesy (I will still visit all of the sponsor booths!).

Quantified Self Europe 2014 Sponsors

9. Seth Roberts left a lasting QS legacy.

The closing plenary was a touching tribute to the late Seth Roberts, who unexpectedly passed away just weeks before the event. While I never knew Seth personally, I definitely admired and have been inspired by his work and it was touching to hear various attendees share their stories about him. Whether you are simply curious about self-tracking or are an active practitioner, his blog and papers are required reading.

10. Amsterdam is an awesome city!

After spending 2 rainy days holed up in the conference hotel, I was so glad I tacked on a few extra days after the conference to check out as much of the city as possible. If you’ve never visited, I highly recommend it. It’s the most laid-back, friendly city I have ever been to. I can’t wait to go back!

blt-amsterdam

Thanks again to all of the conference organizers for putting on such a great, smoothly run event. I realize what a tremendous amount of work must have gone into making it a success! The QS folks have posted their own recap/roundup, which also includes links to recap posts by other attendees. Can’t wait until the next one!

 

Hacking (and Tracking) My Glucose

I never paid much attention to my blood sugar (aka blood glucose, or as I will simply refer to it, glucose) until a few years back, when I started getting more interested in self-tracking/biohacking and my 23andMe DNA analysis showed that I had a genetically elevated risk for type 2 diabetes, which has been shown to be preventable by maintaining low levels of glucose. Elevated glucose can also contribute to a number of other health issues such as cardiovascular disease.

23andMeType 2 Diabetes

The current “accepted” recommendations by the American Diabetes Association for fasting glucose (i.e., no food or drink in the previous 8 hours) are between 70 – 130(!) mg/dL. The exclamation(!) mark is there for a reason. The upper bound is being hotly disputed – in fact, the ADA has a term called “impaired fasting glucose” that was lowered from 110mg/dL to 100mg/dL in 2003. That means that many people that are classified as “normal” are, in fact, pre-diabetic. Organizations like the Life Extension Foundation (a leading organization focused on advancing research on longevity and anti-aging) suggest keeping fasting glucose at or below 85 mg/dL (and optimally even below 80!).

My most recent blood test showed my fasting glucose level was 85mg/dL, considered “good”, even by Life Extension Foundation guidelines. But what I wanted was to better understand how various factors affected my levels, and then be able to proactively control them. Even though my glucose is considered good, I wanted it to be optimal. Why take any chances? [Read more...]

A Step is (Not) a Step – But Does it Matter?

While assembling some of my data for another self-tracking experiment, I grabbed the number of daily “steps” recorded by both Moves and my Basis B1 and whipped up the following chart:

Basis steps vs. Moves steps

I wanted to see if there was a statistically significant relationship between daily steps reported by Moves vs. Basis, even though their values are clearly different. To do so, I analyzed the data using a free online data analysis tool called Statwing and sure enough, there was a statistically significant relationship!

Basis steps vs. Moves steps Statwing correlation

Looking at the chart on the right, you will see that there is a generally linear correlation between number of steps recorded each day between Basis and Moves. For you statistics geeks, here are the correlation/regression details:

Basis vs. Moves steps Statwing correlation

I realize there will always be outliers, such as when I’m playing a sport or exercising wearing my B1 but not being able to hold my iPhone (in which case, Moves can’t track me), device batteries dying or needing charging, etc. but the fact that I can use either tool as a way to visualize general activity trends is good to know.

The lesson learned here is that regardless of what device you are using to track your activity, over time it’s not about whether you took 8,000 vs. 10,000 steps, but rather that you increased your activity by 20%! That, to me, is the most important metric.

Quantifying My Personality Type

The Myers-Briggs Type Indicator (MBTI) seeks to quantify a person’s personality type through a psychometric questionnaire.

Personality typesThey classify an individual into one of 16 possible personality types, based on the following parameters:

  • Extroverted (E) vs. Introverted (I)
  • Sensing (S) vs. Intuition (N)
  • Thinking (T) vs. Feeling (F)
  • Judging (J) vs. Perceiving (P)

As they explain:

“The essence of the theory is that much seemingly random variation in the behavior is actually quite orderly and consistent, being due to basic differences in the ways individuals prefer to use their perception and judgment.”

No one type is meant to be perceived as “better” than another. I found a free online version of the test, answered a series of questions that only took about 5 minutes, and here was my result – ENTJ:

Personality type ENTJ

Digging in a little deeper, I found this portrait of an ENTJ, which they call “The Executive”.

I’ll admit that this description pretty much nails me (I’m an entrepreneur and a CEO), and a few of the traits were rather eye-opening (“The ENTJ needs to consciously work on recognizing the value of other people’s opinions, as well as the value of being sensitive towards people’s feelings”, “Sentiments are very powerful to the ENTJ, although they will likely hide it from general knowledge, believing the feelings to be a weakness”). Reading this has allowed me to take stock in how I interact with and are perceived by others, and I will make an effort to overcome my flaws to become a better friend, coworker, and leader.

Just to confirm the results, about a week later and took the test again – and my personality type was exactly the same (ENTJ). Since this free test is meant to be an approximation of personality type, I will probably fork over the $49.95 to take the “official” MBTI test.

Here’s a list of famous ENTJ’s (Napoleon, Julius Caesar, Bill Gates, Peter Theil, Jack Welch… and Dick Cheney(?!), Joseph Stalin(?!).

So, what is your personality type? You can try it out for yourself here (and it’s free!).

What “Moves” Me – Visualizing 2 weeks of Passive Location Tracking

Moves AppI’ve recently started incorporating an application called Moves into my self-tracking arsenal. As an app, Moves only does just one thing, but does it well – it runs in the background on your smartphone and passively tracks your location 24/7. It has no social sharing functionality, gamification, or bloated features. You can look at a timeline of your day and see how long you were actually at work versus commuting (it tracks steps as well if you are into that sort of stuff).

The location tracking app recently released an API to allow 3rd-party developers and apps to integrate their data. Notable design/data visualization guru Nicholas Felton whipped together some code using Processing that provides a cool visualization layer to my Moves location data. Here is what a typical New York City day looks like for me:

Moves data visualization

The yellow lines indicate times when I was walking (to subway, out for lunch, walking the dog), gray lines show when I was in transit (subway, cab, driving), and blue lines represent times I was riding my bike (in this case, to a soccer game). Pretty neat, but nothing too exciting. However, if we look at several weeks worth of data, we can reveal some interesting trends!

Note that I left out two days of data where I went on out of state trips, as this skews the visualization (in its current incarnation). Check out Moves, and and if you aren’t afraid to get too technical you can get the MovesMapper code here. And this is a great set of location data that can be easily exported and integrated into other self-tracking experiments.