Tag Archives: diabetes
In 2008 Alice Pilgram was diagnosed with type 2 diabetes. Faced with numerous life changes and having to now track multiple pieces of data, she started to feel overburdened. In this talk, presented at the Bay Area QS meetup group, she explains how a new simple tracking system helped her see the bigger picture.
Ernesto is in sunny Austin for SXSW, so I’m filling in to gather this week’s articles and links for your reading pleasure.
Apple ResearchKit concerns, potential, analysis by MobiHealthNews. ResearchKit was a big surprise coming out of Apple’s Special Event this week. It was quite difficult to select just one representative article about the ensuing conversation, so this round-up serves nicely.
#WhatIfResearchKit: What if Research Kit actually, truly, worked… by Christopher Snider. Okay, I failed to keep to one article on ResearchKit. This post chronicles a series of Twitter conversations on the question: if ResearchKit does work, what are the possibilities?
The Electric Mood-Control Acid Test by Kevin Bullis. Thync is a sort of evolved version of a transcranial direct current stimulation (TDCS) device. A technology with a lot of potential and controversy, this article explores why the brain-enhancing effects of the TDCS only work for some people. By the way, if you are a fan of Philip K. Dick, Thync may remind you of the mood organ that was in Do Androids Dream of Electric Sheep?
Automated Learning by Nichole Dobo. Some school classrooms are experimenting with ”Blended learning”, a method of combining classroom teachers and computer-assisted lessons. A detail that stuck with me is the description of three large displays that show where each student is supposed to go that day, based on the results of the previous day’s lesson.
The Mouse Trap: Can One Lab Animal Cure Every Disease? by Daniel Engber. An in-depth how science’s predominant use of lab mice could be limiting our knowledge of disease. Of relevance to self-trackers because many models of optimal health are in part based on mouse studies.
Analyzing a Year of My Sleep Tracking Data by Bob Troia. This is a superb exploration of Bob’s sleep data from 2014 as collected by his Basis watch.
Notes on 416 Days of Treadmill Desk Usage by Neal Stephenson. The author of Snow Crash and The Cryptonomicon is a long time user of a treadmill desk, but when he began having pain in his left leg, he had to reevaluate how he used his favored tool.
Qualities of #QuantifiedSelf by Christina Lidwin. A fascinating analysis of the #quantifiedself hashtag.
First medical apps built with Apple’s ResearchKit won’t share data for commercial gain by Fred O’Connor
Talking Next-Gen Diabetes Tools with Dexcom Leaders by Mike Hoskins
From the Forum
Mood Tracking Methods?
Howto track laptop uptime
CCD or CCR conversion tools?
What gets measured, gets managed – Quantified Self in the workplace
Best ECG/EKG Tool for Exercise
Best iOS app to track water/coffee/alcohol intake?
This Week on QuantifiedSelf.com
QS15 Sponsor Highlight: RescueTime
Quantified Self and Apple’s ResearchKit
Better by Default: An Access Conversation with John Wilbanks
QS15 Conference Preview: Jamie Williams on Tracking My Days
Quantified Self Styles
Lastly, I’ll leave you with a lovely little comic with a message that many self-trackers can relate to.
The Secret by Grant Snider
We hope you enjoy this week’s selection of links, show&tell posts, and visualizations!
Hacking Your Brain by The Economist. Increasing performance and cognitive functioning, reducing depression, improving memory – if you could use a simple tool to get all these done, would you? What if that device was delivering electrical current to your brain? That’s the promise of transcranial direct current stimulation.
Talking Next-Gen Diabetes Tools with Dexcom Leaders by Mike Hoskins. Wonderful interview here with Terry Gregg (chairman) and Kevin Sayer (CEO) of Dexcom. Particular focus is given to their reaction and ideas regarding the open source Nightscout project.
Scientists threatened by demands to share data by Victoria Schelsinger. An older article (2013) about the shift towards open data and data sharing in academic science and it’s potential impact and possible pitfalls.
”’I think the public thinks that we’re all learning from everyone else’s work. That’s not true, and furthermore, it’s not true in ways that are even worse than you might think.’” – Heather Piwowar
Changing Representation of Self-Tracking by Deborah Lupton. It’s always great to hear that Deborah has released new writing. Her thoughtful analysis about self-tracking, data as culture, and data as object is consistently fantastic. Great addition to her growing body of work here.
Why Pets Are the Future of Fitness Wearables by Annie Lowrey. An interesting take on how the rise of tracking tools for pets may impact pet owners. Reminds me of research conducted by my old colleagues at San Diego State University: Physical activity, weight status, and neighborhood characteristics of dog walkers (Spoiler: Having a dog is associated with being more physically avtive.)
This guy is the Mark Zuckerberg of open-source genetics by Daniela Hernandez. A few weeks ago we highlighted an article by Daniela that focused on the fantastic openSNP project. She’s back with a profile of one of the founders, Bastian Greshake. (Full disclosure: I am openSNP member #610.)
Personal Sleep Monitors: Do They Work? by Christopher Winter. Superb experiment here to try and understand the accuracy of different sleep trackers.
What I’ve learned after 10 years of quantifying myself by Maxim Kotin. The title says is all.
A History of Checkins: Facebook Checkin Stats by Octavian Logigan. Octavian breaks down three years of his location checkin history and describes what he learned through examining seasonal trends, category breakdowns, and travel patterns.
I love the sleep tracker, so I can quantify this kind of information! (I have a 2yo and a 5yo….) by reddit user EclecticBlue. Fun visualization here of Fitbit sleep data. Also, great comments in the thread.
Locals & Tourists by Mapbox & Eric Fischer. I could spend hours exploring this interactive map of tweet locations by “tourists” and “locals”. (Special thanks to Beau Gunderson for point out that Eric also did a similar project with geotagged Flickr photos)
The Impact of Weather on Human Activity by Paul Veugen. The team at Human “1.9M activities in Boston & NYC to see the impact of weather on Human activity.” Make sure to click through for the full visualization.
FCC & FDA moving connected health forward by establishing wireless medical test beds
Nike+ Running Expand Global Partnerships
Will Our Fitness Data Be Used Against Us?
As the “quantified self” industry explodes, who will control the data — us or them?
This Week on QuantifiedSelf.com
Gordon Bell: Every Beat of My Heart
QS15 Conference Preview: Stephen Cartwright on 17 Years of Location Tracking
What’s in My Gut
We hope you enjoy this week’s list!
Big Data in the 1800s in surgical science: A social history of early large data set development in urologic surgery in Paris and Glasgow by Dennis J Mazur. An amazing and profoundly interesting research paper tracing the use of “large numbers” in medical science. Who knew that is all began with bladder stones!
Civil Rights, Big Data, and our Algorithmic Future by Aaron Rieke, David Robinson and Harlan Yu. A very thorough and thoughtful report on the role of data in civil and social rights issues. The report focuses on four areas: Financial Inclusion, Jobs, Criminal Justice, and Government Data Collection and Use.
Caution in the Age of the Quantified Self by J. Travis Smith. If you’ve been following the story of self-tracking, data privacy, and data sharing this article won’t be all that surprising. Still, I can’t help but read with fascination the reiteration of tracking fears, primarily a fear of higher insurance premiums.
Patient Access And Control: The Future Of Chronic Disease Management? by Dr. Kaveh Safavi. This article is focused on providing and improving access and control of medical records for patients, but it’s only a small mental leap to take the arguments here and apply them all our personal data. (Editors note: If you haven’t already, we invite you to take some time and read our report: Access Matters.)
Perspectives of Patients with Type 1 or Insulin-Treated Type 2 Diabetes on Self-Monitoring of Blood Glucose: A Qualitative Study by Johanna Hortensius, Marijke Kars, and Willem Wierenga, et al. Whether or not you have experience with diabetes you should spend some time reading about first hand experiences with self-monitoring. Enlightening and powerful insights within.
Building a Sleep Tracker for Your Dog Using Tessel and Twilio by Ricky Robinett. Okay, maybe not strictly a show&tell here, but this was too fun not to share. Please, if you try this report back to us!
Digging Into my Diet and Fitness Data with JMP by Shannon Conners, PhD. Shannon is a software development manager at JMP, a statical software company. In this post she describes her struggle with her weight and her experience with using a BodyMedia Fit to track her activity and diet for four years. Make sure to take some time to check out her amazing poster linked below!
The following two visualizations are part of Shannon Conners’ excellent poster detailing her analysis of data derived from almost four years of tracking (December 2010 through July 2014). The poster is just excellent and these two visualizations do not do it justice. Take some time to explore it in detail!
Tracking Energy use at home by reddit user mackstann.
“The colors on the calendar represent the weather, and the circles represent how much power was used that day. The three upper charts are real-time power usage charts, over three different time spans. I use a Raspberry Pi and an infrared sensor that is taped onto my electric meter. The code is on github but it’s not quite up to date (I work on it in bits and pieces as time permits I have kids).”
Stefan Hoevenaar’s father had Type 1 Diabetes. As a chemist, he was already quite meticulous about using data and those habits informed how he tracked and made sense of his blood sugar and insulin data. In this talk, presented at the 2014 Quantified Self Europe Conference, Stefan describes how his father kept notes and hand-drawn graphs in order to understand himself and his disease.
Last year Alex Collins was diagnosed with Type 1 diabetes. Prior to his diagnosis Alex was frequently engaged in different types of exercise and physical activity. After his diagnosis his doctor mentioned that he might have a hard time exercising and controlling his blood sugar to prevent hypoglycemia. In this talk, presented at the London QS meetup group, Alex described his process for tracking and understanding the data that affects his day-to-day life so that he could “live my life normally without a high risk of complications.” This process of collecting and analyzing data has even pushed him to continue to explore his athletic boundaries, resulting in a running a ultramarathon and setting the world record for the fastest marathon while running in an animal costume.
Slides are available here.
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
Richard Bernstein, an engineer with diabetes, pioneered home blood glucose monitoring. What he learned about himself contradicted the medical doctrine of his day, but Bernstein went on to become an MD himself, and established a thriving practice completely devoted to helping others with diabetes. We think of Dr. Bernstein as a hero because he used self-measurement to support his own learning, and shared what he learned for general benefit.
Tracking personal metabolism is a necessity for diabetics, and it is also something that will become increasingly common for many people who want to understand and improve their metabolism. Diabetics are also leading the fight for personal access to personal data, and we’re looking forward to meeting inspiring activists and toolmakers today at the DiabetesMine D-Data Exchange meeting in San Francisco. In honor of this meeting, we’ve put together an anthology of sort of QS Show&Tell talks about diabetes and metabolism data.
Jana is a Type 1 diabetic and data visualization practitioner who has been working on creating new techniques for understanding that data from her Dexcom continuous blood glucose monitor. In this talk, she described some of her newest techniques and her ongoing work with Tidepool.org. You can also view her original QS show&tell talk here.
Doug has been featured here on the QS website many times. We first learned about Doug through his amazing visualizations of his own data (like the image above). At the 2013 QS Global Conference, Doug shared what he learned from tracking his diabetes, diet, activity, and other personal data and his ongoing work with the Databetes project.
We spoke with Doug about his experience with tracking, visualizing and understanding his diabetes data. You can listen to that below.
James is a graduate student, professional cyclist, and a Type 1 diabetic. In this talk at the QS San Diego meetup group he talked a bit about how he manages his diabetes along with his near super human exercise schedule and how he uses his experience to inspire others. (Check out this great article he wrote for Ride Magazine.)
Brooks, a Type 1 diabetic, was tracking his blood glucose manually for years before switching to a continuous blood glucose meter. In this talk he describes what he’s learned from his data and why he prefers a modal day view.
Bob tracked his fasting blood glucose, diet, and activity to find out what could help him lower his risk of developing type 2 diabetes.
Vivienne’s son was diagnosed with Type 1 Diabetes two years ago and she’s applied her scientific and data analysis background to understand her son’s life.
We’ve learned a lot from the diabetics in our community, such as Jana Beck’s lessons from 100,000+ blood glucose readings, and Doug Kanter’s narrative visualizations of a year of his diabetes data. At the upcoming QS Europe Conference on May 10th and 11th in Amsterdam, we’re going to hear the interesting story of a non-diabetic who began tracking his fasting glucose to improve his health.
With the US Centers for Disease Control estimating that over a third of the US population shows signs of diabetes or pre-diabetes, it’s not surprising that the techniques of learning from blood glucose measurements are spreading more widely. After learning from his 23andMe profile that he had an elevated risk for developing Type 2 Diabetes, Bob Troia began tracking his fasting glucose daily while also tracking exercise, diet, and experimenting with supplements. He’s been reporting the results on his blog, Quantified Bob. If you’re curious about how to apply these techniques in our own life, join as at the upcoming meeting, or keep an eye out for the video of Bob’s talk at the New York Quantified Self show&tell.
The 2014 Quantified Self Europe Conference is just a few weeks away. Please join us!
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.)
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