Published online Mar 20, 2024. doi: 10.5493/wjem.v14.i1.87916
Peer-review started: September 2, 2023
First decision: November 1, 2023
Revised: December 18, 2023
Accepted: February 3, 2024
Article in press: February 3, 2024
Published online: March 20, 2024
Diabetes, a globally escalating health concern, necessitates innovative solutions for efficient detection and management. Blood glucose control is an essential aspect of managing diabetes and finding the most effective ways to control it. The latest findings suggest that a basal insulin administration rate and a single, high-concentration injection before a meal may not be sufficient to maintain healthy blood glucose levels. While the basal insulin rate treatment can stabilize blood glucose levels over the long term, it may not be enough to bring the levels below the post-meal limit after 60 min. The short-term impacts of meals can be greatly reduced by high-concentration injections, which can help stabilize blood glucose levels. Unfortunately, they cannot provide long-term stability to satisfy the post-meal or pre-meal restrictions. However, proportional-integral-derivative (PID) control with basal dose maintains the blood glucose levels within the range for a longer period.
To develop a closed-loop electronic system to pump required insulin into the patient's body automatically in synchronization with glucose sensor readings.
The proposed system integrates a glucose sensor, decision unit, and pumping module to specifically address the pumping of insulin and enhance system effectiveness. Serving as the intelligence hub, the decision unit analyzes data from the glucose sensor to determine the optimal insulin dosage, guided by a pre-existing glucose and insulin level table. The artificial intelligence detection block processes this information, providing decision instructions to the pumping module. Equipped with communication antennas, the glucose sensor and micropump operate in a feedback loop, creating a closed-loop system that eliminates the need for manual intervention.
The incorporation of a PID controller to assess and regulate blood glucose and insulin levels in individuals with diabetes introduces a sophisticated and dynamic element to diabetes management. The simulation not only allows visualization of how the body responds to different inputs but also offers a valuable tool for predicting and testing the effects of various interventions over time. The PID controller's role in adjusting insulin dosage based on the discrepancy between desired setpoints and actual measurements showcases a proactive strategy for maintaining blood glucose levels within a healthy range. This dynamic feedback loop not only delays the onset of steady-state conditions but also effectively counteracts post-meal spikes in blood glucose.
The WiFi-controlled voltage controller and the PID controller simulation collectively underscore the ongoing efforts to enhance efficiency, safety, and personalized care within the realm of diabetes management. These technological advancements not only contribute to the optimization of insulin delivery systems but also have the potential to reshape our understanding of glucose and insulin dynamics, fostering a new era of precision medicine in the treatment of diabetes.
Core Tip: This study describes an innovative diabetes management system that integrates real-time glucose monitoring with advanced artificial intelligence (AI) algorithms and closed-loop insulin delivery. This approach offers precise, personalized control of blood glucose levels, reducing the risk of complications. The simulations demonstrate the system's effectiveness in maintaining stable glucose levels, even in response to meals and exercise, thanks to the International Diabetes Federation controller and basal insulin dosage. Additionally, the study explores the use of ESP32 for monitoring input voltage levels to protect the system. Overall, this study provides a groundbreaking approach that combines AI, closed-loop control, and real-time monitoring to revolutionize diabetes care and improve patient outcomes.