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

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

Abstract 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....

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Bibliographic Details
Main Authors: Xinyu Huang, Franziska Schmelter, Christian Seitzer, Lars Martensen, Hans Otzen, Artur Piet, Oliver Witt, Torsten Schröder, Ulrich L. Günther, Lisa Marshall, Marcin Grzegorzek, Christian Sina
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Non-invasive CGM
Interstitial glucose prediction
Personalized nutrition
Machine learning
Engineered biomarker
Wearables
Online Access:https://doi.org/10.1038/s41598-025-14172-z
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https://doi.org/10.1038/s41598-025-14172-z

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