I have just posted on my other blog about my data analysis of the volatility within a month’s worth of CGM readings. Using R, I wanted to explore ways of judging readings by methods other than just average daily blood sugar. This was completed for my Data Without Borders class at NYU’s ITP. The full post is here.
Another marathon down(my third)! And a new personal record! My time of 3:47 at the Philadelphia Marathon was a two minute improvement.
This race is an important point in my 2012 Quantified Self project. In order to best learn from the day, I carried a total of 8 devices with me: an insulin pump, 2 continuous glucose monitors (CGM) (a Dexcom 7 and my newly arrived Dexcom Gen4), a standard blood glucose monitor, a Garmin heart race monitor chest strap and GPS watch, an iPhone, Nike FuelBand and FitBit. I’ll talk more about these later.
As for my diabetes, managing my blood sugars on the day of the race turned out to be more of a challenge than I was hoping for. During my two previous marathons, I saw my blood sugars spike in the hours before the race, both from being anxious and from how i managed my meal dosages. I was determined to prevent that from happening again this year. I had a normal breakfast (an english muffin with almond butter and a banana) very early in the morning at 5am in order to get to the start line on time. I took a dose of insulin that I would normally take assuming I wasn’t about to exercise. I then had another half of an english muffin at 6am. I took a smaller dose for this, hoping that my blood sugars would start going up a bit closer to the 7am start time (they had been at about 145). I also began a temp basal rate at 6am, setting it to 20% my normal rate for 3 1/2 hours.
Waiting for the start along with Ann, my friend and running companion. We ran the Paris Marathon together back in 2010.
As part of my grad school work at ITP, I recently completed a project called “Ready to Start” for my Collective Storytelling class. “Ready to Start” tells the stories of athlete’s first long-distance race, be it a marathon or a triathlon. It focuses on the motivating factor for people to take on this challenge, dedicating both the time and energy needed to train and complete it. In total we conducted nine interviews, three of whom are patients with diabetes (including myself). For a longer description of the project, please see my ITP blog post. Or just jump to interviews with my inspiring fellow type-1 patients Rachelle Glantz and Jen Davino.
I’ve recently completed my most recent data visualization called Insulin on Board. I looked at 100 days of blood sugar and insulin data to see whether a low-carb diet was effective in keeping my blood sugars in range. To see a PDF of the final version, click here: http://bit.ly/KRTCzP
To learn more about the project, I have another blog post here detailing how and why I made it @ http://bit.ly/Jca8tX
This project was included in the show at NYU’s ITP where I recently completed my first year of grad school. It was also featured on the Flowing Data blog @ http://bit.ly/KR2Tf2
This is a data visualization I produced during the Fall 2011 term at ITP. I used 7729 readings from my Dexcom 7 CGM (continuous glucose monitor) from November, 2011. I created it using Processing, then generated a PDF showing the entire month’s readings on top and additional PDFs for every individual day of the month below. The circle spans the respective time frames starting at the top (12:00), progressing clockwise one turn. The blue represents in-range readings (80-140 mg/dL). The gray represents low blood sugar readings (79-40 mg/dL) and the outside white contains all the high blood sugars readings above 140 mg/dL.
Happy New Year, everyone! I am starting this blog to document a new, year-long project related to Databetes, the company I have founded. Throughout the year, I am recording all my diabetes-related data in an effort to improve my type-1 diabetes control. This includes every blood sugar reading, medication dosage, exercise statistic and A1c blood test. I will also record nutritional information for every meal, snack and (non-water) beverage. I’ll also be adding photographs, geolocation data and other information from my mobile phone.