IMG_9124

‘IDDM’: Music from diabetes data

Introduction:

I have Type 1 (insulin dependent) diabetes.  Trying to manage this disease feels like a full time occupation, and it can be exceptionally difficult to try to keep my blood sugar levels stable enough to function properly sometimes.  Simple things like making sure insulin dosage matches my food intake, how much to reduce insulin to compensate for the physical exertion of exercise or even the mental exertion of writing/lecturing etc., can become difficult calculations and when they go wrong, can have some significant effects.  Too much insulin and I get hypoglycemic symptoms which can be anything from mild dizziness and confusion, to loss of consciousness and even seizures.  Too little insulin and blood sugars rise, causing lethargy, unquenchable thirst (coupled with the constant need to run to the toilet), splitting headaches, and ultimately damage to internal organs and other parts of the body.  I feel constantly as if I am performing a tightrope act and that any false steps have life-threatening consequences. All in all, it is not a great deal of fun to have a condition that can make you feel pretty rough a lot of the time.  I should make it clear that I am very aware that many people are far worse off than I am and, in the grand scheme of things, I’m lucky that my condition is relatively easy to treat.  I am not complaining – just setting the scene for the musical information that follows.

I am hugely fortunate, due to our wonderful NHS, to have been given an insulin pump (pictured above) as part of my treatment.  This has made it easier to manage my condition – not least because of the fact that I no longer have to inject myself 8-10 times a day.  Also, the pump does some of the maths/counting for me, in terms of accounting for insulin and carbohydrates, for example, which is very helpful and takes a bit of the mental pressure off.  I do still have to test my blood sugar frequently (6-10 times a day) so I know what my levels are, but there are far fewer injections to deal with on a daily basis and I am very grateful for that.  I have a Medtronic insulin pump and one of the great features it has is the facility to upload all my data to their servers and to see it all presented in highly informative tables and graphs.  The idea is that  such information will be used to analyse the way I use my pump and how I can tweak the various settings to improve my control.  I do this periodically and have always found it very helpful – but recently I have been using these tables for different reasons.

Making Music:

When looking over days and months of such data in graph form, I cant help to see the rising and falling of the lines as something that could represent elements of music.  So, as an experiment (and a procrastination excuse) I decided that I would try to convert one of the graphs into music.  To cut a long story short, I got engrossed and ended up designing a scheme that would allow me to convert the data from various streams of information into music.

I decided to focus on the four most important elements of my diabetes management that I spend time thinking about throughout any given day, specifically: (a) my current blood glucose level, (b) the amount of active insulin in my system, (c) the dose of insulin I give myself whenever I eat carbohydrate, and (d) the total amount of insulin I take per day (which, of course, changes on a daily basis).  I then looked at the data for each of these elements of my diabetes management for the month of January 2016, and set about turning the numbers into pitches.

Screen Shot 2017-02-13 at 15.00.34
Key/scheme for generating pitch content

I wanted the piece to represent the interaction of all these numbers, rather than for the numbers to just be a way to generate pitch content.  So, I decided that the temporal/durational elements of the music would relate directly to the timeframe in which the data was captured.  So, each beat of the music represents an hour in the month of January 2016, and the pitch material (derived from the data) is played at the appropriate time. So, for example, a blood glucose reading at 7am on the 1st of January would be appear on the 8th beat of the piece (which is scored in common time for ease of reading).

Example of score
Score excerpt

Making Sounds:

For the first version of this piece, I didn’t want to score for an arbitrary ensemble. I wanted to draw on sounds that are related to the daily experience of living with this condition.  As such, I decided to sample the sounds of some of my diabetes paraphernalia.  The four sounds I chose were:

The sound of an insulin vial being struck:

i36-Insulin-Aspart

The ‘twang’ of a blood glucose testing strip:

bayer-contour-next-sensoren-rechts

The ‘beep’ of a blood glucose meter:

CNT NEXT LINK strip in cap on mmol

The ‘zip’ of the case that my glucose meter is stored in:

zipper

The Piece:

The piece is for synthesised instruments created from the samples noted above and an improvising musician. It is the musician’s job to try to improvise as best they can with the limited information provided to them, which is supposed to be representative of daily life for someone with this condition.  The improviser is presented with a ‘score’ of sorts (below) which gives a sketch of the pitch data, and some descriptive text about the various physical feelings associated with high/low blood sugars etc. – what they do with that information is up to them.

Example of Improviser's Score
Example of Improviser’s Score

The first performance of this piece took place in St. Giles Cathedral, Edinburgh, on Friday the 10th of February, as part of the ‘Old Town / New Music’ concert series (organised by Dr John Hails).  This version was played in quadraphonic diffusion with me playing tenor saxophone, as can be seen in the following video.  I am pleased with the way the first performance went, and I look forward to playing this again in future.  If anyone else would like to play it then please feel free to contact me.

Share Button

Dr Zack Moir is a Lecturer in Popular Music at Edinburgh Napier University, and the University of the Highlands and Islands. He has a strong research interest in popular music pedagogy, music in higher education, musical improvisation and popular music composition. Zack is also an active musician and composer performing in ensembles and as a soloist, internationally. Zack is one of the editors of the 'Routledge Research Companion to Popular Music Education'.

2 thoughts on “‘IDDM’: Music from diabetes data”

Leave a Reply

Your email address will not be published. Required fields are marked *