Tag Archives: CGM

Do It Yourself Diabetes

DanaScott_Header

Dana Lewis and Scott Leibrand are the creators of the amazing “Do-It-Yourself-Pancreas-System,” also known by #DIYPS. We had a few question for them.

Ernesto: Why build your own pancreas?

IMG_3561Dana: I’ve had Type 1 diabetes for about 12 years. I use an insulin pump and a continuous glucose monitor (CGM), but the devices are separate. They don’t talk to each other. I have to look at the data from the CGM and then make decisions about my insulin. I have to make about 300 decisions per day on average. It’s really fatiguing. So we created some algorithms that took my blood glucose data, the amount of insulin that I’ve given myself, and the amount of carbohydrates that I’ve decided that I’ve eaten, and ran them over and over again to give me a prediction of what my blood sugar was going to be and whether I need to take any action. Instead of having to constantly do the math myself, our system will push an alert to my phone or watch.

Ernesto: Does it dose you automatically?

Dana: Originally no, but more recently we’ve built a full closed loop version of #DIYPS, that is essentially an artificial pancreas, that talks to my pump and adjusts to give me a little more or a little less insulin.

Ernesto: Who writes the code?

Scott: I’m doing all the coding. I’m sure Dana could, but she has a lot going on and designs the algorithms. My title is Chief Spaghetti-Coder. This is the bleeding edge. It doesn’t need to be elegant code.

Ernesto: What have you learned from building your own pancreas?

Dana: The beauty of a CGM is that it gives you a data point every five minutes. Over the past year I’ve produced more than 130,000 data points of blood sugar levels alone. That gives me an incredible picture of what’s happening. With a traditional meter, it’s rare to find somebody who tests up to even 10 times a day. And the standard use for an insulin pump is very much “set it and forget it.” The #DIYPS allows me to customize without having to constantly adjust my insulin pump manually, and that frees me up to live my life, work, and do whatever it is that I want to do.

A visualization of Dana’s Data over the first year of the #DIYPS system.

A visualization of Dana’s Data over the first year of the #DIYPS system.

Ernesto: How did this project start?

Dana: We first started building the system just to make the alarms on the device louder, to wake me up because I would sleep through them. The device manufacturers didn’t seem to have a solution. Then we started looking at getting the data onto a computer so Scott would be able to view it. At the time, we had recently started dating, and he lives 20 miles away. I wanted him to be able to see what my blood glucose level was, so if it was low, he could text me; and if I didn’t respond, he could call 911. But we didn’t have a way to get the data off of the device.

Scott: The key moment was when we saw a tweet from John Costik, who was working on the Nightscout Project. Nightscout is open source code that helps people transmit their CGM data to other devices. I tweeted John right away: “Hey it would be awesome if we could get access to this code.” That’s really where it started. And along the way the whole process has been extremely public. We’ve been tweeting, blogging, and making everything we’ve been doing completely visible.

Ernesto: I’ve seen you tweet using the hashtag #wearenotwaiting. What does that mean?

Dana: #WeAreNotWaiting is a hashtag that was coined at a conference hosted by an online diabetes advocacy and information sharing community called DiabetesMine.com. For me it means that we’re not waiting for traditional device manufacturers to come out with the product. In three to ten years there’ll be devices like our artificial pancreas systems out in the market, being sold by companies approved by the FDA. I need to be alive when that system gets out in the market in, perhaps, five years.

I need to be alive when a cure becomes available.

Scott: Right about the time that we started working on #DIYPS, the Nightscout Project started to grow really quickly. There are now over 10,000 people in the CGM in the Cloud group. Over 2,000 people are using Nightscout to view their own or their loved ones’ blood sugar levels remotely on phones, watches, and other devices. This is real stuff that’s making a real difference in the world. And that’s only going to accelerate as more people do more interesting things like this closed loop that we’ve just done.

Ernesto: You’ve written about “data as free speech.” What do you mean? How can data be speech?

Dana: People often don’t understand why its legal for us to ‘hack’ a CGM and an insulin pump. (Note that hacking isn’t a negative thing; we’re just sharing the data across devices!) They assume that because all my DIY gadgets are not FDA-approved to use them the way I’m using them is somehow against the rules. But I can treat my own body, my own diabetes, the way I want to. And if I share my data, that’s obviously a kind of speech. But if we decide to share our code? I think the FDA sees this as a gray area. We very much want to continue our conversations with regulators.

Ernesto: Where do you see your project going?

Dana: I feel that every time I answer this question my answer changes, because my understanding of its potential is constantly changing. I never would have thought that any of what we’ve done was possible. Right now one of our goals is to make sure that the knowledge we gained about diabetes through our work with #DIYPS is adopted by clinicians, and that patients have access to this new information for treating diabetes. We’re also taking #DIYPS to a new level with #OpenAPS, an open and transparent effort to make safe and effective basic Artificial Pancreas System (APS) technology widely available to more quickly improve and save as many lives as possible and reduce the burden of Type 1 diabetes.

Dana with the #OpenAPS system.

Dana with the #OpenAPS system.

Scott: A few of months ago, at a conference convened by the advocacy group DiabetesMine, we got up and talked about our project, and I said: “I’m putting a stake in the ground that we’re going to make a closed loop artificial pancreas by August 1st, which is the date we’re getting married.” Everybody applauded and thought that was awesome. Then we went home. And we had it done in two weeks.

Dana: For anybody who wants to get involved in this, we would love to talk to you. There are so many people with diabetes and there is so much data that drives the management of this disease.

But there’s not a lot of awareness of how many diseases, including diabetes, could have their care revolutionized just by having better access to data.

That’s the thread of Quantified Self that I’m most interested in. The diabetes community happens to be one of the first to take advantage of what’s possible.

Dana tweeted her blood glucose data during this interview.

We invite you to share your data access stories, and this Access Conversation with the #qsaccess hashtag and follow along here in our Access Channel quantifiedself.com and @quantifiedself.

RWJF_Logo_Support2

Posted in QS Access, QS Access Conversations | Tagged , , , , , , , | 2 Comments

What We're Reading

Enjoy this week’s list!

Articles
CGM in the Cloud: Personal Preferences by Kerri Sparling. A great blog post here by Kerri who explains why it’s so important to have access to her blood sugar data. She’s part of a growing community of people with diabetes who are using different methods to broadcast their CGM data into the could.

On Minorities and Outliers: The Case for Making Big Data Small by Brooke Foucault Welles. The rush towards finding the answers in “Big Data” might lead to the continued exclusion of the women, minorities, and the “outliers” of the world. Brooke makes the case here for examining these “small datasets”  to give them the weight they deserve.

“When women and minorities are excluded as subjects of basic social science research, there is a tendency to identify majority experiences as “normal,” and discuss minority experiences in terms of how they deviate from those norms . In doing so, women, minorities, and the statistically underrepresented are problematically written into the margins of social science, discussed only in terms of their differences, or else excluded altogether.”

Here’s Looking at You: How Personal Health Information Is Being Tracked and Used [PDF] by Jane Sarashon-Kahn. In this report, from the California Healthcare Foundation, Jane lays out how our health data is being acquired and used, for commercial and public benefit. I especially liked the emphasis on privacy, or lack there of.

The Making of April Zero by Anand Sharma. Anand details his journey from starting to self-track to creating an amazing website that serves as his personal QS dashboard. One interesting bit is that his tracking activities increased dramatically after Apple’s M7 chip came out with the iPhone 5S and he noticed that his phone’s battery took much less of a hit from running apps that track his activity in the background.

Show&Tells
Tracking Upset and Recovery by Paul LaFontaine. Paul has been using the Heartmath stress monitor to help him record and understand what causes him to get upset (fall out of coherence). In this post, he details how his recovery method has helped him progress, recover, and slightly reduce the number of upsets during his working session. I recommend reading all of Paul’s great posts on this work.

Europe Honeymoon by reddit user Glorypants. This reddit user tracked his European honeymoon with the Moves app and then used our How to Map Your Moves Data post to learn how to make some great maps to share his experience.

Visualizations
Lillian_YIR
This Year in Numbers – 2014 by Lillian Karabaic. A great “year in review” post here that details the tracking Lillian has done from July 2013 to July 2014. I love the mix of hand-drawn and computer-generate visualizations that provide insight into Lillian’s sleep, diet, cycling, mood, and communication data. (Editor’s Note: Lillian sent this link via the comments on Quantifiedself.com. If you have something to share please let us know!)

HelpMeViz
HelpMeViz.com. I wanted to highlight this great website and community project as we have many great visualization and data scientists in our community. On the HelpMeViz website people submit their visualizations for feedback and assistance. I’ve had fun interacting with the growing community and have even learned a few neat tricks in the process.

TravisHodges
The Quantified Self by Travis Hodges. Travis is a portrait photographer based in London. For his newest project he sought out fifteen individuals who are using self-tracking to understand and improve themselves. I especially like the inclusion of the data visualizations coupled with the individual stories from these self-trackers.

TwitterViz
Visualizing Your Twitter Conversations by Jon Bulava. Jon, a Developer Advocate at Twitter, put together a wonderful how-to for getting started on visualizing your friend network on Twitter. (If you’re interested in using the new Twitter Analytics data to better understand your tweeting we suggest Bill Johnson’s great how-to.)

From the Forum
Data Aggregation
Smart Mirror with Health Sensors
Garmin Vivo Activity Tracker – Your Results?
Sleep Tracking for New Parents

Want to receive the weekly What We Are Reading posts in your inbox? We’ve set up a simple newsletter just for you. Click here to subscribe

Posted in What We're Reading | Tagged , , , , , , | Leave a comment