Probabilistic Meal Detection and Estimation in Type 1 Diabetes With Extreme Shape Variability
This innovative approach holds the potential to help individuals with T1D better manage their blood glucose levels by providing information regarding glucose response to meals and estimated meal sizes for closed-loop control. Future research can focus on enhancing key components of the algorithm and incorporating additional data types to improve its performance further.
Authors
- B. Wayne Bequette (ORCID: https://orcid.org/0000-0002-6472-1902)
- Mrunal Sontakke (ORCID: https://orcid.org/0000-0001-7786-7727)
- Faye Cameron
Institutions
- Rensselaer Polytechnic Institute (US)
- Precision for Medicine (United States) (US)
Publication Details
- Journal
- Journal of Diabetes Science and Technology
- Published
- 2025-08-28
- DOI
- https://doi.org/10.1177/19322968251363234
- Primary Topic
- Diabetes and associated disorders
- Type
- article
- Field-Weighted Citation Impact
- 0.00