Monthly Archives: April 2014

Analysing heart rate and diabetes data using R

At the start of the project I thought I would be spending all of my time using Hadoop and other Big Data technologies to analyse my data. The conclusion that I rapidly came to is that if you don’t have huge amounts of data then Hadoop is probably not the best option. Once I have a […]

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Processing Diasend CGM and insulin data

As part of my project to correlate exercise and insulin usage in type 1 diabetes I need to get hold of my blood glucose and insulin usage data. I use an insulin pump with an embedded continuous glucose monitoring (CGM) sensor. Periodically I upload all the data from the pump to Diasend. Diasend is quite a […]

Accessing heart rate data from Strava API

In my last post I looked at options for recording heart rate data. I settled on using a Garmin HRM strap, linked to my Garmin Edge 500 and Garmin FR70. I use the Edge while on my bike on the road and in the gym (you can link the Edge to a Wattbike, which is […]

Quantifying exercise – continuous heart rate monitoring

One part of The Glucose Project is to try and quantify exercise so that it can be correlated with insulin usage and blood glucose level. The question I want to answer is, depending on the amount of exercise I have done, how should I adjust my insulin dose? My first approach is to look at heart […]

The Glucose Project – correlating exercise and insulin usage in type 1 diabetes

I’ve finally found it. I have been trying to think of a good project to get my teeth stuck into – something that will get me up to speed with all these new Big Data technologies as well as being of some use – and I think i’ve got one: The Glucose Project. In brief, […]