health life sciences medicine
This study aimed to determine the feasibility and effectiveness of wearable devices in detecting early physiological changes prior to the development of prediabetes [1-3]. The study generated digital biomarkers for remote, mHealth-based prediabetes and hyperglycemia risk to classify which individuals should undergo further clinical testing. The primary inclusion criteria were subjects aged 35-65 years, inclusive, including only post-menopausal females, with a point of care A1C measurement between 5.2-6.4%, inclusive. Blood was collected during the study for measurement of glucose, hemoglobin A1C, lipoproteins, and triglycerides. Participants wore a Dexcom 6 continuous glucose monitor (CGM) and an Empatica E4 wristband for 10 days while receiving a standardized breakfast meal every other day. At the end of the 10 days, the participant returned to the clinic for an oral glucose tolerance test (OGTT). Research data collected includes physiological measurements from wearable devices such as heart rate, accelerometry, and electrodermal conductance.
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Open Data Commons Attribution License v1.0
https://doi.org/10.13026/aw6y-fc44
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BIG IDEAs Lab Glycemic Variability and Wearable Device Data was accessed on DATE from https://registry.opendata.aws/big-ideas-glycemic-wearable.
arn:aws:s3:::physionet-open/big-ideas-glycemic-wearable/us-east-1aws s3 ls --no-sign-request s3://physionet-open/big-ideas-glycemic-wearable/