Key result
Skin temperature was the most consistently important biometric variable (important in 6 of 7 tested exercises) for predicting exercise-induced changes in glucose concentrations in Type 1 diabetes.
Why the study?
Which biometric variables measured by wearable sensors correlate best with changes in glucose concentrations during exercise in people with Type 1 Diabetes?
Observational (n=26)
No
Which biometric variables measured by wearable sensors correlate best with changes in glucose concentrations during exercise in people with Type 1 Diabetes?
Skin temperature, energy expenditure, and heart rate are key biometric variables that could improve glucose regulation during exercise if integrated into an artificial pancreas system.
Incorporating biometric variables into AP systems may aid exercise glucose control in T1D; leaves open whether benefits hold in larger trials.
An artificial pancreas (AP) computes the optimal insulin dose to be infused through an insulin pump in people with Type 1 Diabetes (T1D) based on information received from a continuous glucose monitoring (CGM) sensor. It has been recognized that exercise is a major challenge in the development of an AP system. The use of biometric physiological variables in an AP system may be beneficial for prevention of exercise-induced challenges and better glucose regulation. The goal of the present study is to find a correlation between biometric variables such as heart rate (HR), heat flux (HF), skin temperature (ST), near-body temperature (NBT), galvanic skin response (GSR), and energy expenditure (EE), 2D acceleration-mean of absolute difference (MAD) and changes in glucose concentrations during exercise via partial least squares (PLS) regression and variable importance in projection (VIP) in order to determine which variables would be most useful to include in a future artificial pancreas. PLS and VIP analyses were performed on data sets that included seven different types of exercises. Data were collected from 26 clinical experiments. Clinical results indicate ST to be the most consistently important (important for six out of seven tested exercises) variable over all different exercises tested. EE and HR are also found to be important variables over several types of exercise. We also found that the importance of GSR and NBT observed in our experiments might be related to stress and the effect of changes in environmental temperature on glucose concentrations. The use of the biometric measurements in an AP system may provide better control of glucose concentration.
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Turksoy et al. (2017) conducted an observational in Type 1 Diabetes (n=26). Biometric variables during exercise (heart rate, heat flux, skin temperature, near-body temperature, galvanic skin response, energy expenditure, 2D acceleration) was evaluated on Variable Importance in Projection (VIP) scores for predicting glucose change slope during exercise. Skin temperature was the most consistently important biometric variable (important in 6 of 7 tested exercises) for predicting exercise-induced changes in glucose concentrations in Type 1 diabetes.
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