DiAs user interface: a patient-centric interface for mobile artificial pancreas systems.

BACKGROUND: Recent in-hospital studies of artificial pancreas (AP) systems have shown promising results in improving glycemic control in patients with type 1 diabetes mellitus. The next logical step in AP development is to conduct transitional outpatient clinical trials with a mobile system that is controlled by the patient. In this article, we present the user interface (UI) of the Diabetes Assistant (DiAs), an experimental smartphone-based mobile AP system, and describe the reactions of a round of focus groups to the UI. This work is an initial inquiry involving a relatively small number of potential users, many of whom had never seen an AP system before, and the results should be understood in that light. METHODS: We began by considering how the UI of an AP system could be designed to make use of the familiar touch-based graphical UI of a consumer smartphone. After developing a working prototype UI, we enlisted a human factors specialist to perform a heuristic expert analysis. Next we conducted a formative evaluation of the UI through a series of three focus groups with N = 13 potential end users as participants. The UI was modified based upon the results of these studies, and the resulting DiAs system was used in transitional outpatient AP studies of adults in the United States and Europe. RESULTS: The DiAs UI was modified based on focus group feedback from potential users. The DiAs was subsequently used in JDRF- and AP@Home-sponsored transitional outpatient AP studies in the United States and Europe by 40 subjects for 2400 h with no adverse events. CONCLUSIONS: Adult patients with type 1 diabetes mellitus are able to control an AP system successfully using a patient-centric UI on a commercial smartphone in a transitional outpatient environment.

Historical data enhances safety supervision system performance in T1DM insulin therapy risk management.

Safety measures to prevent or mitigate hypoglycemia are an important component of open loop, closed loop, and advisory mode insulin therapy control settings in type 1 diabetes. In recent work, we introduce a method for the automatic, gradual attenuation of the insulin pump delivery rate when a risk of hypoglycemia is detected, a method that we refer to as brakes. In the methods presented here, we demonstrate the use of historical glucose measurement data to inform and enhance the ability of the brakes to prevent hypoglycemia in real-time. The updated brakes are based on a patient-specific, time-varying model that reflects the typical trajectory of glycemic fluctuations throughout the day. Historical heightened risk of hypoglycemia throughout the day prompts an increase in the aggressiveness of insulin attenuation as compared to the original brakes that are based on real-time data alone. Through the use of available real-time data supplemented with historical glucose information to assess hypoglycemic risk, we are able to better anticipate and prevent hypoglycemia.

Fully integrated artificial pancreas in type 1 diabetes: modular closed-loop glucose control maintains near normoglycemia.

Integrated closed-loop control (CLC), combining continuous glucose monitoring (CGM) with insulin pump (continuous subcutaneous insulin infusion [CSII]), known as artificial pancreas, can help optimize glycemic control in diabetes. We present a fundamental modular concept for CLC design, illustrated by clinical studies involving 11 adolescents and 27 adults at the Universities of Virginia, Padova, and Montpellier. We tested two modular CLC constructs: standard control to range (sCTR), designed to augment pump plus CGM by preventing extreme glucose excursions; and enhanced control to range (eCTR), designed to truly optimize control within near normoglycemia of 3.9-10 mmol/L. The CLC system was fully integrated using automated data transfer CGM→algorithm→CSII. All studies used randomized crossover design comparing CSII versus CLC during identical 22-h hospitalizations including meals, overnight rest, and 30-min exercise. sCTR increased significantly the time in near normoglycemia from 61 to 74%, simultaneously reducing hypoglycemia 2.7-fold. eCTR improved mean blood glucose from 7.73 to 6.68 mmol/L without increasing hypoglycemia, achieved 97% in near normoglycemia and 77% in tight glycemic control, and reduced variability overnight. In conclusion, sCTR and eCTR represent sequential steps toward automated CLC, preventing extremes (sCTR) and further optimizing control (eCTR). This approach inspires compelling new concepts: modular assembly, sequential deployment, testing, and clinical acceptance of custom-built CLC systems tailored to individual patient needs.

The accuracy benefit of multiple amperometric glucose sensors in people with type 1 diabetes.

OBJECTIVE: To improve glucose sensor accuracy in subjects with type 1 diabetes by using multiple sensors and to assess whether the benefit of redundancy is affected by intersensor distance. RESEARCH DESIGN AND METHODS: Nineteen adults with type 1 diabetes wore four Dexcom SEVEN PLUS subcutaneous glucose sensors during two 9-h studies. One pair of sensors was worn on each side of the abdomen, with each sensor pair placed at a predetermined distance apart and 20 cm away from the opposite pair. Arterialized venous blood glucose levels were measured every 15 min, and sensor glucose values were recorded every 5 min. Sensors were calibrated once at the beginning of the study. RESULTS: The use of four sensors significantly reduced very large errors compared with one sensor (0.4 vs. 2.6% of errors ≥50% from reference glucose, P < 0.001) and also improved overall accuracy (mean absolute relative difference, 11.6 vs. 14.8%, P < 0.001). Using only two sensors also significantly improved very large errors and accuracy. Intersensor distance did not affect the function of sensor pairs. CONCLUSIONS: Sensor accuracy is significantly improved with the use of multiple sensors compared with the use of a single sensor. The benefit of redundancy is present even when sensors are positioned very closely together (7 mm). These findings are relevant to the design of an artificial pancreas device.