Peculiarities of the Continuous Glucose Monitoring Data Stream and Their Impact on Developing Closed-Loop Control Technology

Author:

Kovatchev Boris1,Clarke William2

Affiliation:

1. Author Affiliations: Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, Virginia

2. Department of Pediatrics, University of Virginia, Charlottesville, Virginia

Abstract

Therapeutic advances in type 1 diabetes (T1DM) are currently focused on developing a closed-loop control system using a continuous glucose monitor (CGM), subcutaneous insulin delivery, and a control algorithm. Because a CGM assesses blood glucose indirectly (and therefore often inaccurately), it limits the effectiveness of the controller. In order to improve the quality of CGM data, a series of analyses are suggested. These analyses evaluate and compensate for CGM errors, assess risks associated with glucose variability, predict glucose fluctuation, and forecast hypo- and hyperglycemia. These analyses are illustrated with data collected using the MiniMed CGMS® (Medtronic, Northridge, CA) and Freestyle Navigator™ (Abbott Diabetes Care, Alameda, CA). It is important to remember that traditional statistics do not work with CGM data because consecutive CGM readings are highly interdependent.

Publisher

SAGE Publications

Subject

Biomedical Engineering,Bioengineering,Endocrinology, Diabetes and Metabolism,Internal Medicine

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