Noninvasive Hypoglycemia Detection in People With Diabetes Using Smartwatch Data.

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 asso

SUBMITTER: Lehmann V 

PROVIDER: S-EPMC10154647 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature