A Diabetic's Experiment with Self Quantification

Project Infobox
Self researcher(s)	Brooks Kincaid
Related tools	blood glucose monitor, Notes
Related topics	Metabolism, Chronic disease, Blood tests and blood pressure, Blood glucose tracking, Sleep, Activity tracking
Builds on project(s)
Has inspired	Projects (0)

Show and Tell Talk Infobox
Featured image
Date	2012/11/12
Event name	Bay Area Meetup
Slides

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A Diabetic's Experiment with Self Quantification is a Show & Tell talk by Brooks Kincaid that has been imported from the Quantified Self Show & Tell library.The talk was given on 2012/11/12 and is about Metabolism, Chronic disease, Blood tests and blood pressure, Blood glucose tracking, Sleep, and Activity tracking.

Description

A description of this project as introduced by Quantified Self follows:

Brooks Kincaid, a 29 years old cyclist, is into being fit. He is also a co-founder of Imprint which develops battery technology to print customize, thin, flexible, rechargeable batteries that can be used in a variety of small portable electronic devices like Med Tech devices and wearable technology, with potential self-quantification applications. Brooks is also a type 1 diabetic. In this talk, he shares his experiment as a diabetic with self quantification.

Video and transcript

https://vimeo.com/54881152

A transcript of this talk is below:

Brooks Kincaid - A Diabetic's Experiment with Self Quantification

So tonight is my first time that a QS meeting and you know, just generally interested then this space and without really consciously thinking about it and gotten involved in self-quantification via my personal condition. So as you can probably guess from the title. I’m a diabetic. A quick intro of me, I’m 29 years old, a big biker and heavy into athletics so do some quantification on that side of things is, and using Garman devices from time and tangentially related to the Quantified Self in what I do as well. I have a co-founder, the head of business or technology company called Imprint Energy. We develop battery technology, the chemistry is something called zinc (poly) as is to print customize, thin, flexible, rechargeable batteries. They may eventually be used in a variety of small portable electronic devices like Med Tech devices and wearable technology, with potential self-quantification applications. I’m a type I diabetic, for those of you who don’t know, diabetes or what that means, it basically means I’m insulin dependent, so my blood sugar is varying all the time, the pancreas doesn’t work like yours does in terms of automatically giving you insulin. And so I need to self-administer insulin based on what my blood sugar is, what I have eaten, and what else I’ve been doing. I’ve been a type I diabetic for 18 years, and for 16 of those I was effectively flying kind of blind. Testing your blood sugar pretty regularly and have to administer based on those readings. For the last two years I’ve been “quantified” with movements to new devices. So a quick background, as a diabetic blood glucose is critical. It is the number one thing you have to do in order to make sure you have you avoid sort of short-term and long-term dangers. 5 to 8 finger sticks and a gut feeling for 16 years as well is what I meant when I said I was effectively flying blind. And that’s before I got quantified. And I was basing my insulin delivery on how it felt, and those few times a day that I was testing my blood sugar. The metaphor I like to use is that it was like I was driving down the freeway with my eyes closed, and then opening them once every couple of hours, versus driving down a freeway now with being quantified and maybe just constantly blinking, but still having a good sense of where I’m going. The difficulty with the previous version is established trends, which is pretty important to know how you react to different stressors, food, athletic events, etc. Stuff that can analyze the impact of changes and learning that we all talk about, and really mission-critical is mitigating the risk of lows. You know there is that short-term risk that you go to sleep overnight and you go to low, that you can have some pretty negative health implications. So getting into what did I do all what was I trying to do, well when this device became available on the market, it’s called a continuous glucose monitor, my goal was and has always been to improve the control of my diabetes and avoid the dangerous incidences. This became finally covered by insurance carriers, and produced by technology companies made it available to me and I started living with and driving with my eyes wide open. I went from that 5 to 8 blood sugar samples a day, to sampling every five minutes, so that’s a pretty significant increase in the amount of data that I was able to collect. And as a result, I was able to get a much better sense of where I was trying to go. It’s got some simple nifty features, and we are seeing more and more features in both medical devices and technology devices. For me, in particular the alarms associated with saying, okay, you are trending one way or another have been really important in helping me stay within the pretty defined range that I’m trying to stay within. So how have I done it, or how have I gotten better off my control, basically analyzing the data that I’m collecting. And data on its own, not particularly interesting, but data in the context and over a longer period of time has been interesting for me. And over the week-long snapshots that I take I can remember with a decent level of granularity what I’ve done over the past week. And I can say well okay great, it looks like in the mornings or overnight I am drifting down a little bit, but then I start to rise in the morning. I can put that in context by saying, well what did I do over the past week, what stressors were there, what did I eat, or how early did I wake up. And it’s interesting to find those correlations on a day-to-day basis, when I was just testing my blood sugar once every five minutes, and really kind of put it together to establish those trends. But in now taking these week-long snapshots, in addition to having this as an immediate data source I’m able to get a better sense of the short-term and long-term impacts of things that I’m changing in my life. So I’ve learned a few things in doing this, and I’ve been doing this for about two years. Like I said, there’s a lot of noise for me day-to-day. But being able to get that data over a long period of time and notice the trends and the changes as I make changes, and see how they affect things over a week, a month, six months has been really important. I think like I was saying before, looking at what those trends are helped me personally realise when I was most at risk to have potential issues, and that was when there was going to be serious changes in the routine. I’m not one who is particularly good at being regimented in doing the same thing every day. And so now I am more aware of when I’m going to make a significant change in my day-to-day lifestyle, and what implications that might have for my diabetes. One thing I think I found particularly interesting is that you think okay, you can’t a great new device and it’s going to help you be much better with your control. But to some extent I found it actually promotes a little bit of laziness in that I know that it is they are, and I know that it’s monitoring me and warning me if I go one way or another. As a result, whereas I started looking at it really frequently when I first got it. I now don’t as much because I kind of say well, it’s collecting it for me and I can look at it at the end of the day. I think what I’ve realised is that it will be interesting to see how quickly things will converge onto a single platform or if they can. You know, if I had my way it would be the mobile computer that we all carry because, whether consciously or not, I probably look at this 50 times a day, checking email, voicemail, text message or something else. And the unconscious interaction with the data that I’m trying to monitor and in my case glucose I think would be really valuable. It will be interesting to see how other forms of self-quantification may transform onto this platform. Lastly, I think with the data that I’ve been collecting that has been really valuable, but there is still sort of broken links in the chain, difficult to complete the loop in that knowing when my blood sugar is great, but trying to quantify the really difficult things to quantify i.e. what exactly did I eat today.

For someone who doesn’t always have the time to really painstakingly write down everything I did, and have really granular information on you know what was in everything that I ate, that’s still that uncomplete part of the loop, and that’s the one difficulty and still having.

About the presenter

Brooks Kincaid gave this talk.