Digital biomarkers for interstitial glucose prediction in healthy individuals using wearables and machine learning

A personalized low-glycemic diet, maintaining stable blood glucose levels, aids in weight reduction and managing (pre-)diabetes and migraines in individuals. However, invasiveness, high cost, and limited lifecycle of continuous glucose monitoring (CGM) devices restrict their widespread use. To addre...

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Bibliographic Details
Published in:Scientific reports 2025-08, Vol.15 (1), p.30164-19, Article 30164
Main Authors: Huang, Xinyu, Schmelter, Franziska, Seitzer, Christian, Martensen, Lars, Otzen, Hans, Piet, Artur, Witt, Oliver, Schröder, Torsten, Günther, Ulrich L., Marshall, Lisa, Grzegorzek, Marcin, Sina, Christian
Format: Article
Language:English
Subjects:
692/53/2423
692/700/478
Ablation
Adult
Algorithms
Biomarkers - analysis
Biomarkers - blood
Blood Glucose - analysis
Blood Glucose Self-Monitoring - instrumentation
Blood Glucose Self-Monitoring - methods
Blood levels
Diabetes
Diabetes mellitus
Diet
Engineered biomarker
Feature selection
Female
Glucose
Glucose - analysis
Glucose - metabolism
Glucose monitoring
Healthy Volunteers
Humanities and Social Sciences
Humans
Hypoglycemia
Interstitial glucose prediction
Invasiveness
Learning algorithms
Machine Learning
Male
Metabolism
Middle Aged
multidisciplinary
Non-invasive CGM
Nutrient deficiency
Personalized nutrition
Science
Science (multidisciplinary)
Sensors
Wearable Electronic Devices
Wearables
Young Adult
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