Artificial Pancreas System Embedded With Smartphone Assist In Managing Diabetes – ZMR Blog
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Artificial Pancreas System Embedded With Smartphone Assist In Managing Diabetes

Artificial Pancreas System Embedded With Smartphone Assist In Managing Diabetes

Advancement in technology has paved the way to several means to diagnose and treat patients with a diverse range of disorders. And adding to the advancements in the artificial pancreas system developed by scientists incorporated with smartphones to unceasingly monitor levels of glucose in diabetic patients and deliver needed insulin doses automatically.

After the constant 60,000 Hours of mutual use of a new artificial pancreas system, the study participants in a 12-week clinical setting demonstrated considerable improvements in 2 major aspects of well-being in individuals surviving with type 1 diabetes. Type 1 diabetes patients (n=30) went about their usual daily schedules while the artificial pancreas system constantly supervised their levels of glucose and automatically adjusted the insulin delivery settings.

The findings showed positive effects on 2 vital indicators, namely, reduced time spent in hypoglycemia and decreased HbA1c (hemoglobin A1c). The study was led by Eyal Dassau and Frank Doyle from the Harvard John A Paulson School of Engineering and Applied Sciences (SEAS). Individuals with type 1 diabetes must watchfully keep a track of levels of blood glucose and, when essential, administer insulin doses either via infusion pump or needle injections.

The artificial pancreas is developed to imitate the glucose-regulating function of a healthy individual. The closed-loop system comprises an insulin pump and unceasing glucose monitor situated beneath the skin of the user. An advanced control algorithm entrenched in a Bluetooth-connected smartphone indicates how much insulin should the pump deliver to the individual dependent on an array of variables, consisting of physical activity, meals, stress, sleep, and metabolism.

Artificial Pancreas System

The adaptive control algorithm system utilized in the study is rooted on model-predictive control (or MPC), an approach originally designed by Doyle and teams, expanded to a zone-based form of the MPC algorithm. Instead of regulating levels of glucose to a particular point in a similar manner that a home thermostat maintains the room temperature at a specific setting, the zone-MPC outlines a suitable zone for glucose levels of an individual and handles variables to remain within that range.

Along with the core zone MPC algorithm, the researchers incorporated adaptive elements that enabled the algorithm to “study” from the recurrent daily cycles, resulting in enhancements in basal control and meal compensation as well. Doyle said, “This is by far the lengthiest duration trial we have performed, and it is a testimony to the robustness of the algorithm that our main performance indices were sustained from our earlier, shorter trials.”

We hope this new system is able to assist patients with type 1 diabetes and provide them a better standard of living.

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