I’ve been away from blogging for a while. Although I’ve been feeling like I should be writing more often, I was instead using my spare time to finalize my slides and talk for the QS15 Conference that I attended in San Francisco last week, which was organized by QS Labs. It’s my goal to digest various pieces of what I learned at the conference over a series of blogs. I promise not to pack it all into one monster post! First, some background on the conference.
Earlier this year, I was asked to give a talk at QS15 and I was thrilled to be able to go! I have posted from time to time in the online forum at quantifiedself.com about my projects and shared some blog links, a few of which have been featured in their weekly What We are Reading newsletter (sign up here). I love getting their newsletter because it collects and summarizes so many interesting articles on visualization of and public policy around personal data. It’s so easy to get immersed in reading about all the amazing projects people are doing in this space!
Leading up to the conference, I did a podcast with Ernesto Ramirez from QS Labs about my ongoing projects that monitor my diet and fitness data, talking about how and why I got involved in doing this, and what collecting and visualizing my data means to me. What I do with my own data represents an intersection between understanding my past struggles with weight, fitness and health, and visualizing data using JMP, the software developed by my group at SAS. Digging into my personal data sources has been extremely rewarding over the past year and a half. Not only have I learned about patterns I needed to change in my eating and activity habits, but I’ve also found bugs in our pre-production software while working with my data and developed scripting and visualization skills that have let me tackle work projects that I never imagined being able to do by myself. For example, I’ve written scripts to parse and work with several new internal data sources, one of which basically replicated the processing approach I used to parse my space delimited text food log files.
A few weeks before the conference, I had an online session with QS Labs’ Steven Jonas to review my current draft of my talk. Steven made several key suggestions that changed the structure and content of my talk. One was to share how I had collected such detailed data on my diet records over the years and the other was to focus more on the visualizations I had created. In my final version of the talk, I use my struggle with my weight to help motivate why I started collecting data on my diet and fitness habits, but I focused more on the graphs that I felt contributed best to my story. I also added a slide to talk about the “old way” I used to collect my food logging data with a nutritional reference book and a notebook in which I meticulously noted down foods, portions and macros. Having apps for that makes it so much easier! I was extremely grateful to both Ernesto and Stephen for their help leading up to the conference.
Although not directly related to the conference, I’ve also had some opportunities lately to interact with people who are running companies in the space. I have been offering some items of feedback to the Push Strength team via their forum on my experience with the app and data export tools they offer, and spoke to Mike Lovas from Push a few weeks ago. I am using my band for every workout to count reps and sets and measure metrics like power, velocity, and timing of eccentric and concentric parts of my reps. Although not a perfect experience quite yet, I know the team is actively working on an app update that will address many of the quirks I noted in my early use. I would be using an app anyway to collect data about my workouts, so I’m glad to have the band and Push app to collect more data on my workouts.
Experiences like this one have made me realize just how interested start-ups and small companies are in understanding their users’ experiences with devices and apps so that they can improve them and increase the chance of long-term use. Before the conference, I also spoke to Cara Mae from Whatify, a website focused around helping non-experts design simple experiments to answer questions by randomizing assignment of factors and collecting data via text message. It was great to meet her at QS15 and I enjoyed her talk too.
At the conference, I had a chance to try out Skulpt Aim, a device for measuring local body fat percentage and muscle quality in different body areas. I had seen it online before the conference and it seemed intriguing and I have since ordered one. There is a special offer for $149 from the site right now and you can use my referral link here if you’re interested. (You can’t blame me for trying to get Amazon gift cards for referrals!) Stasia from Skulpt was working at their booth in the exhibit hall and measured my left bicep as 14.6% BF and a MQ score of 134, to which she responded, “You work out, don’t you?” Apparently 100 is average, and I am in the athletic category for that area.
Skulpt can estimate overall bodyfat percentage averaging measures taken in several areas, and measurements for different body areas are tracked separately in the Skulpt app so you can assess your progress over time in response to training. The device was developed for use in clinical settings for assessing muscle quality in people with muscle wasting diseases and just recently was released for use by the general population. I’m excited to have a more useful metric which Skulpt claims lines up well with gold standard methods for body fat calculation like DEXA and hydrostatic weighing. I have had a DEXA done, which provides compartmental measures of body fat that in my opinion provide value above and beyond the overall body fat percentage offered by underwater weighing. If it lives up to its claims, Skulpt seems like it will be even more useful because it provides data on more specific body areas and logs it straight to my iPhone. While the use of DEXA for bone density in post-menopausal women is common, if I wanted to get another DEXA done for body composition like I did in January 2014, the closest place is a few hours’ drive and the cost is $50. This makes for a long day trip, so it’s not surprising I haven’t gone back since my initial session.
I’ll post again soon about the conference. I’m still fighting jet lag to get back on my early morning schedule, but I’m determined to take the time to log what I learned and saw there before I get into the thick of preparing for my JMP Discovery 2015 talk on my workout data.