HarveyRA, DassauE, ZisserH, SeborgDE, Doyle FJIII. Design of the glucose rate increase detector: a meal detection module for the health monitoring system. J Diabetes Sci Technol, 2014; 8: 307–320.
2.
DassauE, BequetteBW, BuckinghamBA, Doyle FJIII. Detection of a meal using continuous glucose monitoring: implications for an artificial beta-cell. Diabetes Care, 2008; 31: 295–300.
3.
CameronF, NiemeyerG, BuckinghamBA. Probabilistic evolving meal detection and estimation of meal total glucose appearance. J Diabetes Sci Technol, 2009; 3: 1022–1030.
4.
TurksoyK, SamadiS, FengJ, LittlejohnE, QuinnL, CinarA. Meal detection in patients with type 1 diabetes: a new module for the multivariable adaptive artificial pancreas control system. IEEE J Biomed Health Inform, 2016; 20: 47–54.
5.
WeimerJ, ChenS, PeleckisA, RickelsMR, LeeI. Physiology-invariant meal detection for type 1 diabetes. Diabetes Technol Ther, 2016; 18: 616–624.
6.
SamadiS, TurksoyK, HajizadehI, FengJ, SevilM, CinarA. Meal detection and carbohydrate estimation using continuous glucose sensor data. IEEE J Biomed Health Inform, 2017; 21: 619–627.
7.
XieJ, WangQ. A variable state dimension approach to meal detection and meal size estimation: in silico evaluation through basal-bolus insulin therapy for type 1 diabetes. IEEE Trans Biomed Eng, 2017; 64: 1249–1260.
8.
ZhengM, NiB, KleinbergS. Automated meal detection from continuous glucose monitor data through simulation and explanation. J Am Med Inform Assoc, 2019; 26: 1592–1599.
9.
KolleK, BiesterT, ChristiansenS, FougnerAL, StavdahlO. Pattern recognition reveals characteristic postprandial glucose changes: non-individualized meal detection in diabetes mellitus type 1. IEEE J Biomed Health Inform, 2020; 24: 594-602.
10.
ZhengF, BonnetS, VilleneuveE, DoronM, LepecqA, ForbesF. Unannounced meal detection for artificial pancreas systems using extended isolation forest. Annu Int Conf IEEE Eng Med Biol Soc, 2020; 2020: 5892–5895.
11.
MeneghettiL, FacchinettiA, FaveroSD. Model-based detection and classification of insulin pump faults and missed meal announcements in artificial pancreas systems for type 1 diabetes therapy. IEEE Trans Biomed Eng, 2021; 68: 170–180.
12.
PalisaitisE, El FathiA, von OettingenJE, HaidarA, LegaultL. A meal detection algorithm for the artificial pancreas: a randomized controlled clinical trial in adolescents with type 1 diabetes. Diabetes Care, 2021; 44: 604–606.
13.
DanielsJ, HerreroP, GeorgiouP. A deep learning framework for automatic meal detection and estimation in artificial pancreas systems. Sensors (Basel),, 2022; 22: 466.
14.
ZieglerA, WilliamsT, YaridN, SchultzDL, BundockEA. Fatalities due to failure of continuous subcutaneous insulin infusion devices: a report of six cases. J Forensic Sci, 2019; 64: 275–280.
15.
PatelPJ, BenasiK, FerrariG, et al.Randomized trial of infusion set function: steel versus teflon. Diabetes Technol Ther, 2014; 16: 15–19.
16.
KarlinAW, LyTT, PyleL, et al.Duration of infusion set survival in lipohypertrophy versus nonlipohypertrophied tissue in patients with type 1 diabetes. Diabetes Technol Ther, 2016; 18: 429–435.
17.
WaldenmaierD, ZschornackE, BuhrA, PleusS, HaugC, FreckmannG. A prospective study of insulin infusion set use for up to 7 days: early replacement reasons and impact on glycemic control. Diabetes Technol Ther, 2020; 22: 734–741.
18.
SwinneyMR, CoxAL, HawkinsED, et al.Insulin, not the preservative m-cresol, instigates loss of infusion site patency over extended durations of CSII in diabetic swine. J Pharm Sci, 2021; 110: 1418–1426.
19.
BodeBW, StrangeP. Efficacy, safety, and pump compatibility of insulin aspart used in continuous subcutaneous insulin infusion therapy in patients with type 1 diabetes. Diabetes Care, 2001; 24: 69–72.
20.
ThethiTK, RaoA, KawjiH, et al.Consequences of delayed pump infusion line change in patients with type 1 diabetes mellitus treated with continuous subcutaneous insulin infusion. J Diabetes Complications, 2010; 24: 73–78.
21.
EislerG, KastnerJR, TorjmanMC, et al.In vivo investigation of the tissue response to commercial Teflon insulin infusion sets in large swine for 14 days: the effect of angle of insertion on tissue histology and insulin spread within the subcutaneous tissue. BMJ Open Diabetes Res Care, 2019; 7: e000881.
22.
FosterNC, BeckRW, MillerKM, et al.State of type 1 diabetes management and outcomes from the T1D exchange in 2016-2018. Diabetes Technol Ther, 2019; 21: 66–72.
23.
ValenzuelaJM, SeidM, WaitzfelderB, et al.Prevalence of and disparities in barriers to care experienced by youth with type 1 diabetes. J Pediatr, 2014; 164: 1369–1375.e1.
24.
ThabitH, LalR, LeelarathnaL. Automated insulin dosing systems: advances after a century of insulin. Diabet Med, 2021; 38: e14695.
25.
LeelarathnaL, ChapmanA, MorrisJ, UrwinA, RutterM. Glycemic control in a large cohort of patients with type 1 diabetes (T1DM) treated with continuous subcutaneous insulin infusion (CSII). Diabetes, 2015; 64: A60–A60.
26.
PickupJC, ReznikY, SuttonAJ. Glycemic control during continuous subcutaneous insulin infusion versus multiple daily insulin injections in type 2 diabetes: individual patient data meta-analysis and meta-regression of randomized controlled trials. Diabetes Care, 2017; 40: 715–722.
27.
ReznikY, CohenO, AronsonR, et al.Insulin pump treatment compared with multiple daily injections for treatment of type 2 diabetes (OpT2mise): a randomised open-label controlled trial. Lancet, 2014; 384(9950): 1265–1272.