Synthetic Continuous Glucose Monitoring (CGM) Signals
Published: 20 August 2021| Version 2 | DOI: 10.17632/chd8hx65r4.2
Contributors:
Simon Cichosz, Description
Based on a trained Conditional Generative Adversarial Network (CGAN), the dataset contains 40,000 CGM days with a sampling frequency 288/day, equivalent to 940,000 hours of synthetic CGM. The dataset contains both signal resembling people with type 1 diabetes and healthy individuals. Profiles are categorized into four groups resembling different HbA1c levels: (1) below 6.5% (healthy without diabetes), (2) between 6.5% to <7%, (3) between 7% to <8% and (4) above 8%. Reference: Cichosz SL, Xylander AAP. A Conditional Generative Adversarial Network for Synthesis of Continuous Glucose Monitoring Signals. J Diabetes Sci Technol. 2021 May 30:19322968211014255. doi: 10.1177/19322968211014255. Epub ahead of print. PMID: 34056935
Files
Categories
Glucose, Glucose Metabolism, Diabetes Mellitus, Blood Glucose Monitoring