scholarly journals Closed-Loop Insulin Delivery Using a Subcutaneous Glucose Sensor and Intraperitoneal Insulin Delivery: Feasibility study testing a new model for the artificial pancreas

Diabetes Care ◽  
2009 ◽  
Vol 33 (1) ◽  
pp. 121-127 ◽  
Author(s):  
E. Renard ◽  
J. Place ◽  
M. Cantwell ◽  
H. Chevassus ◽  
C. C. Palerm
Author(s):  
Ishita Rai ◽  
Anil Wanjari ◽  
Sourya Acharya

The discovery of insulin was 100 years old till 2021. Insulin, the first diabetic medication, is now the safest and most effective glucose-lowering medication available. Despite its efficacy, the most significant challenge with insulin has been the prevalence of hypoglycemia, which has resulted in the majority of patients being prescribed optimum dosages. Insulin delivery devices include syringes, pens, and pumps. Soon, artificial pancreas (AP) by using a very closed-loop delivery method will be a big step towards the advancement of insulin delivery devices. This article looks at the invention of syringes, disposable, long-lasting pens, and smart connected pens, continuous intraperitoneal insulin infusion (CIPII) and patch insulin pumps, artificial pancreas and other medical devices. Hence, insulin administration that is both minimally invasive and non-invasive towards the advancement is required. We review the available information on the evolution of insulin delivery systems, focusing on the advantages and disadvantages of technology as well as anticipated advances. Due to the wide variety of technological solutions accessible via the international platform, only the most common methods essential to the patient’s care are detailed here in the article.


Diabetes Care ◽  
1982 ◽  
Vol 5 (3) ◽  
pp. 213-217 ◽  
Author(s):  
B. J. Oberhardt ◽  
E. J. Fogt ◽  
A. H. Clemens

Diabetes Care ◽  
2008 ◽  
Vol 31 (5) ◽  
pp. 934-939 ◽  
Author(s):  
S. A. Weinzimer ◽  
G. M. Steil ◽  
K. L. Swan ◽  
J. Dziura ◽  
N. Kurtz ◽  
...  

2014 ◽  
Vol 16 (3) ◽  
pp. 186-192 ◽  
Author(s):  
Craig Kollman ◽  
Peter Calhoun ◽  
John Lum ◽  
Werner Sauer ◽  
Roy W. Beck

2020 ◽  
Vol 22 (3) ◽  
pp. 185-194 ◽  
Author(s):  
Emilie Palisaitis ◽  
Anas El Fathi ◽  
Julia E. Von Oettingen ◽  
Preetha Krishnamoorthy ◽  
Robert Kearney ◽  
...  

Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 612 ◽  
Author(s):  
Jesús Berián ◽  
Ignacio Bravo ◽  
Alfredo Gardel ◽  
José Luis Lázaro ◽  
Sergio Hernández

The number of patients living with diabetes has increased significantly in recent years due to several factors. Many of these patients are choosing to use insulin pumps for their treatment, artificial systems that administer their insulin and consist of a glucometer and an automatic insulin supply working in an open loop. Currently, only a few closed-loop insulin delivery devices are commercially available. The most widespread systems among patients are what have been called the “Do-It-Yourself Hybrid Closed-Loop systems.” These systems require the use of platforms with high computing power. In this paper, we will present a novel wearable system for insulin delivery that reduces the energy and computing consumption of the platform without affecting the computation requirements. Patients’ information is obtained from a commercial continuous glucose sensor and a commercial insulin pump operating in a conventional manner. An ad-hoc embedded system will connect with the pump and the sensor to collect the glucose data and process it. That connection is accomplished through a radiofrequency channel that provides a suitable system for the patient. Thus, this system does not require to be connected to any other processor, which increases the overall stability. Using parameters configured by the patient, the control system will make automatic adjustments in the basal insulin infusion thereby bringing the patient’s glycaemia to the target set by a doctor’s prescription. The results obtained will be satisfactory as long as the configured parameters faithfully match the specific characteristics of the patient. Results from the simulation of 30 virtual patients (10 adolescents, 10 adults, and 10 children), using a python implementation of the FDA-approved (Food and Drug Administration) UVa (University of Virginia)/Padova Simulator and a python implementation of the proposed algorithm, are presented.


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