Tag Archives: diabetes

What We Are Reading

Another collection of thought-provoking items from around the web.

Articles & Posts

Plan to move from #quantified self to Qualified Self by Inga de Waard. Every now and then someone writes something that causes me to pump the brakes and really reflect on self-tracking and personal data collection. This is one of those time. Inga does a nice job here setting up her experience with self-tracking to understand her type 1 diabetes. She moves on to explore how “qualified data” might be a better source of information for personal growth, “I am more than my body, I am mind. So I want to understand more.”

The Bracelet of Neelie Kroes (in German) by Frank Schirrmacher. Can machines be trusted? Are we building and willingly wearing the handcuffs of the future by strapping tracking devices to our wrists? These questions are explored in this article. (If you’re like me you are probably wondering who Neelie Kroes is. Here’s some background info.)

Biggest Gene Sequence project to launch by Bradley J. Fikes and Gary Robbins. J. Craig Venter is at it again. Now that genome sequencing has passed the $1000 barrier he has set up a new company in order to recruit and sequence 40,000 people per year.

This Mediated Life by Christopher Butler. Another amazing piece of self-reflection spawned by the recently released Reporter App. Rather than reviewing the application, the author addresses what it means to self-track when we know we are our own observer. Do we bias our reflection and data submission when we know that each answer, each data point is being collected into a larger set? (This post reminded me of one of my favorite movie lines, “How am I not myself.” from I Heart Huckabees

The Open Collar Project. At a recent meeting I learned of this project to create an open-source dog tracking collar. Pet trackers are becoming more prevalent in the market, but the purpose of this project goes far beyond just understanding pet activity. I learned from the lead researcher, Kevin Lhoste, that they’re using this as a method to encourage and engage children in science and mathematics. Very neat stuff.

Twitch Crowdsourcing: Crowd Contributions in Short Bursts of Time [PDF] by Rajan Vaish, Keith Wyngarden, Jingshu Chen, Brandon Cheung, and Michael S. Bernstein. This research paper describes the results of a really interesting project to gather information from people using micro-transactions during the phone unlocking process. It appears that we can learn a lot from people in under 2 seconds.

The Open FDA. Not an article here, but I wanted to call attention to the new open initiative by the FDA. This new effort was spearheaded by Presidential Innovation Fellow, Sean Herron. If you’re interested in doing this type of work you can apply to be a fellow here.

Show&Tells (a selection of first person stories on self-tracking and personal data)

200 days of stats: My QS experience by Octavian Logigan. Octavian recounts the various data he’s collected including activity, sleep, email behavior, and work productivity. I really like how he clearly explains what tools he’s using.

A Year in Diabetes Data by Doug Kanter. We’ve featured Doug here on the blog before. From his amazing visualizations to his talks about his process, we’ve been consitently impressed and inspired by this work. In this post Doug recounts 2012 – “[...] the healthiest year of my life.” (Full disclosure: Doug sent me the poster version of his data and it is beautiful.)

Visualization

timkim_map
This visualization comes to us from Tim Kim, a design student based in Los Angeles.

The map shows different collections and documentations made during my cross country trip. Posts made during the trip on various social media sites are orientated and placed by the geological locations. The states are elongated by purely how I felt about the duration of going across the specific state. For example, driving through texas sucked (no offense). Different facts are layered and collaged across the map to create and express a collective, over-all image of the trip. Some quantifiable information, some quantitative information to create a psych-geolocal map.

Thumbs Up Viz A really nice website that highlights and explains the good pieces of data visualization popping up all over the web these days.

From the Forum

Tracking emotional experience
Test our a new app for sleep improvement
Measuring emotions through vital signs

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Jana Beck on Visualizing Her Diabetes Data

As you may know, we get excited when someone in our community uses interesting data visualizations to help tell their self-tracking story. Jana Beck is no exception. As a woman living with Type 1 diabetes she’s constantly learning how to better understand what her Dexcom data is telling her. In this talk, Jana follows up on her previous show&tell presentation with some new visualization techniques she’s using. If you’re interested in Jana’s methods be sure to check out her Github repository and her work with Tidepool.org.

(Editor’s Note: I very interested in Jana’s use of Chernoff faces for multivariate data visualization. If you’re using this type of visualization for your own data I would love to see it. Get in touch.)

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Vivienne Ming on Tracking Her Son’s Diabetes

Vivienne Ming is an accomplished neuroscientist and entrepreneur. When she’s not conducting research or working on new ideas she’s busy taking care of her son Felix. Two years ago Felix was diagnosed with Type 1 Diabetes. Vivienne and her partner tackled his diagnosis head on and started tracking everything they could. In this talk, presented at the 2013 Quantified Self Global Conference, Vivienne explains what they’re learning together.

We’ll be posting videos from our 2013 Global Conference during the next few months. If you’d like see talks like this in person we invite you to join us in Amsterdam for our 2014 Quantified Self Europe Conference on May 10 and 11th.

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QS Gallery: Doug Kanter

Doug Kanter shared this beautiful and unique visualization of his blood glucose with us. Be sure to take a peak at his other great visualizations and his wonderful talk at the 2013 Quantified Self Global Conference.

This is a visualization of one month of my blood sugar readings from October 2012. I see that my control was generally good, with high blood sugars happening most often around midnight (at the top of the circle).
-Doug Kanter

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Doug Kanter: A Year Of Diabetes Data

The complex relationship between behavior and diabetes control has long been a testing ground for gathering and making sense of personal data. Doug Kanter is a Type-1 diabetic who’s been thinking about how self-tracking influences his diabetes control for a few years. While in graduate school at the Interactive Telecommunications Program (ITP) at NYU he started experimenting with visualizations that helped him understand his blood sugar and insulin dosing. In 2012 he began adding more data to his exploration in order to better understand how diet played a role in his diabetes self-management. Watch this great talk to learn more about Doug’s journey and his ongoing Databetes project.

We’ll be posting videos from our 2013 Global Conference during the next few months. If you’d like see talks like this in person we invite you to join us in Amsterdam for our 2014 Quantified Self Europe Conference on May 10 and 11th.

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Doug Kanter on Data, Diabetes, and Marathon Training

Doug Kanter has been a Type 1 diabetic for 26 years. Through this time he’s come to learn more about his disease by using many data-gathering tools and his own work in visual analysis at the NYU ITP program. We’ve featured Doug’s compelling work here on the blog before and we were excited to hear him talk at the NY QS Meetup about his new project to understand how marathon training and running effect his blood sugar and insulin treatment.

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What We Are Reading

Here’s some great pieces from around the web to get your mind working and give you some insight into what we find interesting and compelling.

The Diabetes Paradox by Thomas Goetz: A fascinating look at how we can think about self-tracking from the point of view of those who may track the most: diabetics. He also offers some great insights into how to design the self-tracking experience. Be sure to check out the comments for some great discussion.

quantified-selfHow life-logging can change the way we view and express ourselves by Elia Morling: A very nice overview of lifelogging and its potential impact. I especially enjoyed the leading image (pictured here). Maybe a future cover for a Quantified Self Magazine perhaps?

Know Thyself: How Mindfulness Can Improve Self-Knowledge: A short but wonderful overview of an interesting research article by Erika Carlson that explores how mindfulness may be pathway to improving how and what we know of ourselves.

Specifically, mindfulness appears to directly address the two major barriers to self-knowledge: informational barriers (i.e., the quantity and quality of information people have about themselves) and motivational barriers (i.e., ego-protective motives that affect how people process information about themselves).

The Secret Life of Cats: What You Can Learn by Putting a GPS on Your Kitty by Alexis Madrigal: This book review and interview is fun, interesting, and touches on some very important ideas about self-tracking and technology. I’ve been ruminating on this special nugget since my initial reading:

 Technology can do many amazing things, but no GPS unit or CatCam can tell us what questions we should be asking in the first place.

Do you have any interesting articles or links? Send them our way!

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Brooks Kincaid: A Diabetic Experiment with Self-Quantification

Brooks Kincaid has been tracking his blood glucose continuously for the past two years, after 16 years of finger pricking and guessing. In the video below, Brooks openly shares what he has learned about the benefits and challenges of continuous blood glucose monitoring, and explains his preferred data view, the modal day snapshot. (Filmed by the San Francisco QS meetup group.)

Brooks Kincaid – A Diabetic’s Experiment with Self Quantification from Gary Wolf on Vimeo.

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Jana Beck on Learning from over 100,000 Blood Glucose Readings

Jana Beck was diagnosed with Type 1 diabetes when she was 19 years old and has been interested in tracking her health ever since. Last year when she received a continuous blood glucose monitor she decided to take a more active role in understand what was effecting her blood glucose levels and insulin dosing. Spurred by reading about carbohydrate restricted diets, she decided to see if she could see changes in her blood glucose readings and as a result of changing her diet. In this talk at the New York QS Meetup she describes exactly what she found and shares some really neat visualizations that help tell her story.

Jana Beck – Quantifying Diabetes: Lessons learned from 100,000+ blood glucose readings from Steven Dean on Vimeo.

You can read more about the last New York QS Meetup here. If you’re interested in using theses data visualizations with your own blood glucose data be sure to check our Jana’s iPancreas project on GitHub.

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Numbers From Around the Web: Round 8

If you have diabetes, or know someone who does, you’ve probably encountered a blood glucose monitor. Like many medical devices, design and data visualization are usually an afterthought. While there are many new exciting products coming to market like the iBGStar designed by Agamatrix, there are individuals who want to learn more than just their current blood glucose values. Diabetes care is also moving towards an automated and coordinated process driven by continuous blood glucose monitoring and implantable insulin pumps. These devices live on data, huge amounts of data, but what do their users know? More specifically, what do their users understand about their data, their condition, and themselves?

Doug Kanter is a designer, photographer and a student in the Interactive Telecommunications Program (ITP) at NYU. He’s also a Type-1 diabetic who has a keen interest in applying actionable design and interaction schemes to the data he gathers from his monitoring systems.

It is time to re-imagine the entire user experience of being a patient with diabetes. There is tremendous potential in applying information technology, creative design and research into behavior change into a comprehensive product for patients. Technology-based solutions are increasingly important resources in these times of skyrocketing treatment costs and lmited doctor availability.

Doug has been using his skills to better visualize and understand his own data, particularly his continuous blood glucose monitor. His first project, 7729, explored one month of his continuous blood glucose monitoring – the 7729 readings to be exact.

His second project expanded on the 7729 project to include not only his blood glucose monitoring, but also the insulin he was receiving. Insulin on Board, is based on 100 days of data collection and includes 820 insulin pump reading and 25,012 blood glucose reading. By coordinating these two data sets he was able to look for patterns and identify the efficacy of his insulin dosing.

The goal of Insulin on Board was to better understand the relationship between the insulin I take and the resulting blood sugar readings. It visualizes not simply when I take a dose of insulin, but when that insulin “kicks in.” Because insulin has a latency, it is helpful to see it actually has an effect on blood sugar. Often times I’ll take two or more doses of insulin within a few hours. Insulin on Board calculates the sum overlapping effect of these dosages.

I think patients like me could benefit massively from having improved visualizations that give you both a solid overview of how you are doing but also allow you to dial down into the details if you want.

Being a student and designer, Doug has done a great job explaining the process he takes for developing these visualizations. If you’re interesting in learning more about how he created these visualizations, what he learned, and future work you can follow along at Databetic and his blog.

Every few weeks be on the lookout for new posts profiling interesting individuals and their data. If you have an interesting story or link to share leave a comment or contact the author here.

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