Glucose prediction algorithms from continuous monitoring data: Assessment of accuracy via continuous glucose error-grid analysis

Journal of Diabetes Science and Technology

Volumn 1, Issue 5, 2007, Pages 645-651

  Zanderigo, Francesca ^a   Sparacino, Giovanni ^a   Kovatchev, Boris ^b   Cobelli, Claudio ^a  

^a UNIVERSITY OF PADOVA   (Italy)

^b UNIVERSITY OF VIRGINIA   (United States)

Author keywords

Auto regressive model; Glucose sensor; Hypoglycemia; Polynomial model; Time series

Indexed keywords

EID: 54749122334     PISSN: None     EISSN: 19322968     Source Type: Journal    
DOI: 10.1177/193229680700100508     Document Type: Article

References (7)

1. Klonoff DC. Continuous glucose monitoring: roadmap for 21st century diabetes therapy. Diabetes Care. 2005 May; 28(5):1231-9.
2. Sparacino G, Zanderigo F, Corazza S, Maran A, Facchinetti A, Cobelli C. Glucose concentration can be predicted ahead in time from continuous glucose monitoring sensor time-series. IEEE Trans Biomed Eng. 2007 May; 54(5):931-7.
3. Kovatchev BP, Gonder-Frederick LA, Cox DJ, Clarke WL. Evaluating the accuracy of continuous glucose-monitoring sensors: continuous glucose-error grid analysis illustrated by TheraSense Freestyle Navigator data. Diabetes Care. 2004 Aug; 27(8):1922-8.
4. Maran A, Crepaldi C, Tiengo A, Grassi G, Vitali E, Pagano G, Bistoni S, Calabrese G, Santeusanio F, Leonetti F, Ribaudo M, Di Mario U, Annuzzi G, Genovese S, Riccardi G, Previti M, Cucinotta D, Giorgino F, Bellomo A, Giorgino R, Poscia A, Varalli M. Continuous subcutaneous glucose monitoring in diabetic patients: a multicenter analysis. Diabetes Care. 2002 Feb; 25(2):347-52.
5. Clarke WL, Cox D, Gonder-Frederick LA, Carter W, Pohl SL. Evaluating clinical accuracy of systems for self-monitoring of blood glucose. Diabetes Care. 1987 Sep-Oct; 10(5):622-8.
6. Cox DJ, Gonder-Frederick LA, Kovatchev BP, Julian DM, Clarke WL. Understanding error grid analysis. Diabetes Care. 1997 Jun; 20(6):911-2.
7. Facchinetti A, Sparacino G, Zanderigo F, Cobelli C. Prediction of glucose concentration from CGM data through AR time-series models: role of sampling frequency and other design variables [abstract]. Diabetes Technology Meeting; 2006 Nov; Atlanta, GA.