# Temporal gradient analysis of blood glucose responses to non-standard physical activity: a free-living study in type 1 diabetes

## TL;DR

This study explores how non-standard physical activity affects blood glucose levels in people with type 1 diabetes in real-life settings.

## Contribution

The study introduces a method to analyze blood glucose responses to non-standard physical activity using gradient-based analysis in free-living conditions.

## Key findings

- Non-standard physical activity correlates with steeper declines in blood glucose during downward trends.
- BG declines following prior increases show greater variability, with accuracy ranging from 73.53% to 88.33%.
- The findings support the development of personalized tools for managing insulin or carbohydrate adjustments.

## Abstract

Daily physical activity (PA) impacts blood glucose (BG) in individuals with Type 1 Diabetes Mellitus (T1DM), with effects varying by intensity, duration, and timing. Predicting BG changes during free-living activity remains challenging but may help prevent hypoglycaemia. Previous studies have focused on the impact of PA on BG levels, but only during exercise sessions, not throughout the entire day.

Using retrospective data from eight individuals with T1DM (mean age 67 years; 3 female, 5 male), we analysed whether non-standard PA, defined as activity exceeding the individual’s mean habitual level in a preceding interval, was associated with steeper downward trends in BG. PA was quantified using wrist-worn accelerometry, and BG responses were analysed using gradient-based methods across 20, 40, and 60 min time windows.

Two hypotheses were evaluated. Hypothesis 1 assessed whether BG decline intensified during existing downward trends and achieved an accuracy above 83.33%, with F1-scores exceeding 0.83 at shorter intervals. Hypothesis 2 examined BG declines following prior increases and showed greater variability; accuracy ranged from 73.53% to 88.33%, with the lowest F1-score of 0.75 at the 60 min window.

We have found a reliable correlation between increased levels of PA and BG levels under free-living conditions. These findings establish a foundation for future work aimed at quantifying BG responses to PA and developing personalised decision-support tools for insulin or carbohydrate adjustment.