Noninvasive Hypoglycemia Detection in People With Diabetes Using Smartwatch Data

Lehmann V, Foll S, Maritsch M, van Weenen E, Kraus M, Lagger S, Odermatt K, Albrecht C, Fleisch E, Zueger T, Wortmann F, Stettler C (2023)


Publication Type: Journal article

Publication year: 2023

Journal

Book Volume: 46

Pages Range: 993-997

Journal Issue: 5

DOI: 10.2337/dc22-2290

Abstract

OBJECTIVE To develop a noninvasive hypoglycemia detection approach using smartwatch data. RESEARCH DESIGN AND METHODS We prospectively collected data from two wrist-worn wearables (Garmin vivoactive 4S, Empatica E4) and continuous glucose monitoring values in adults with diabetes on insulin treatment. Using these data, we developed a machine learning (ML) approach to detect hypoglycemia (<3.9 mmol/L) noninvasively in unseen individuals and solely based on wearable data. RESULTS Twenty-two individuals were included in the final analysis (age 54.5 ± 15.2 years, HbA1c 6.9 ± 0.6%, 16 males). Hypoglycemia was detected with an area under the receiver operating characteristic curve of 0.76 ± 0.07 solely based on wearable data. Feature analysis revealed that the ML model associated increased heart rate, decreased heart rate variability, and increased tonic electrodermal activity with hypoglycemia. CONCLUSIONS Our approach may allow for noninvasive hypoglycemia detection using wear-ables in people with diabetes and thus complement existing methods for hypoglycemia detection and warning.

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APA:

Lehmann, V., Foll, S., Maritsch, M., van Weenen, E., Kraus, M., Lagger, S.,... Stettler, C. (2023). Noninvasive Hypoglycemia Detection in People With Diabetes Using Smartwatch Data. Diabetes Care, 46(5), 993-997. https://doi.org/10.2337/dc22-2290

MLA:

Lehmann, Vera, et al. "Noninvasive Hypoglycemia Detection in People With Diabetes Using Smartwatch Data." Diabetes Care 46.5 (2023): 993-997.

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