TY - JOUR
T1 - Advancing Automated Insulin Delivery Systems through Deep Reinforcement Learning: Current Progress and Emerging Opportunities
AU - Lukas Weber
AU - Sophie Janssen
AU - Jonas Richter
AU - Elena Fischer
JF - Journal of Trustworthy and Explainable Intelligent Systems
JO - J Trustworthy Explain Intell Syst
Y1 - 2023
VL - 2
IS - 1
SP - 26
N2 - Progress in continuous glucose monitoring (CGM) technologies alongside wearable electronics is driving the evolution of automated insulin delivery systems (AIDs) toward fully automated closed-loop configurations. The ultimate goal is to provide safe, individualized, and optimized management of blood glucose concentration (BGC) for patients living with diabetes. Although model predictive control offers an adaptable architecture for constructing AIDs control logic, accurate and efficient BGC regulation demands models capable of accounting for inter- and intra-patient variability as well as perturbation uncertainties. Innovations in artificial intelligence offer novel pathways for creating data-driven, fully closed-loop AIDs. Among these approaches, deep reinforcement learning (DRL) has gained substantial interest owing to its inherent robustness against disturbances. Consequently, this article presents a comprehensive literature review focused on DRL-based BGC control methodologies within AIDs. Initially, this paper systematically evaluates the advantages of deploying DRL frameworks in AIDs. Following this, it delivers an extensive analysis of diverse DRL methods and enhancements designed to surmount obstacles linked to their integration into AIDs, addressing factors such as restricted sample availability, personalization, and safety protocols. Furthermore, an application-centric assessment of DRL-based AIDs control algorithms is provided, highlighting critical hurdles encountered during practical implementation. Lastly, the paper addresses potential remedies for relevant BGC control challenges, outlines prospects for real-world application, and identifies future research trajectories.
UR - https://tipublications.com/y474223385
ER -