Hypometrics: Integrating glucose, activity and sleep data for better insights
Hypometrics is an open‑source R package developed to support the integrated analysis of continuous glucose monitoring data, wearable‑derived activity and sleep metrics, and smartphone‑based hypoglycaemia reporting within a single analytical framework.
It was developed as part of the Hypo‑METRICS study within the IHI‑funded Hypo‑RESOLVE programme, which includes the University of Leicester as a partner, and was led by Gilberte Martine‑Edith, a Research Associate in Professor Pratik Choudhary’s team at the Leicester Diabetes Centre. The package addresses a key gap by providing a set of functions that bring together data sources that are often analysed separately.
In practice, these types of data are closely linked but are usually handled in isolation. Hypometrics makes it possible to examine them together, so that physical activity, sleep, and person‑reported hypoglycaemia can be considered alongside glucose data rather than in parallel. This makes it easier to interpret glucose patterns in context, supporting a more complete and accurate characterisation of hypoglycaemia burden and helping to reduce the risk of biased or incomplete conclusions that can arise from single‑source analysis.
By bringing these complementary streams of digital health data into one place, hypometrics enables researchers, analysts and methodologists to work with a fuller picture of lived physiology and behaviour. The result is analysis that is not only more coherent, but also easier to interpret and more relevant to real‑world clinical questions.
The package is available on GitHub at https://github.com/leicester-cdag/hypometrics, with supporting documentation and resources available at https://leicester-cdag.github.io/hypometrics/index.html.
Dr Gilberte Martine-Edith.
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