Detection of a meal using continuous glucose monitoring: implications for an artificial beta-cell.
OBJECTIVE
The purpose of this study was to introduce a novel meal detection algorithm (MDA) to be used as part of an artificial beta-cell that uses a continuous glucose monitor (CGM).


METHODS
We developed our MDA on a dataset of 26 meal events using records from 19 children aged 1-6 years who used the MiniMed CGMS Gold. We then applied this algorithm to CGM records from a DirecNet pilot study of the FreeStyle Navigator continuous glucose sensor. During a research center admission, breakfast insulin was withheld for 1 h, and discrete glucose levels were obtained every 10 min after the meal.


RESULTS
Based on the Navigator readings, the MDA detected a meal at a mean time of 30 min from the onset of eating, at which time the mean serum glucose was 21 mg/dl above baseline (range 2-36 mg/dl), and >90% of meals were detected before the glucose had risen 40 mg/dl from baseline.


CONCLUSIONS
The MDA will enable automated insulin dosing in response to meals, facilitating the development of an artificial pancreas.
Dassau
Eyal
E
Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, CA 93106-5080, USA.
Bequette
B Wayne
BW
Buckingham
Bruce A
BA
Doyle
Francis J
FJ
D000465:Algorithms; D001187:Artificial Organs; D001786:Blood Glucose / Q000378:metabolism*; D004435:Eating; D006801:Humans; D050417:Insulin-Secreting Cells; D007700:Kinetics; D008962:Models, Theoretical; D018670:Monitoring, Ambulatory / Q000379:methods
D001786:Blood Glucose