Long-Term Diabetes Prevention via Physical Activity: An Output-Feedback MPC Approach

Extensive clinical evidence supports the beneficial role of physical activity in delaying the progression of type-2 diabetes. However, current clinical recommendations remain largely qualitative, failing to account for the patient’s evolving condition and lacking a quantitative framework for real-time, personalized prescriptions. In this letter, we propose an original model-based approach to the control of diabetes progression via physical activity, based on a control-theoretical formulation of the benefits of the exercise, leveraging a sampled-data observer-based model predictive control framework. We design the control law on a compact, widespread model of diabetes evolution, whilst the effectiveness of the proposed control strategy is tested in silico by closing the loop on a population of virtual subjects simulated by a different, higher-dimensional model of diabetes regulation under exercise. The validation procedure also accounts for the effect of additional non-idealities, including quantized measurements and disturbances, and clearly shows the efficacy of a suitably designed physical activity to prevent diabetes progression. To the best of our knowledge, this letter proposes for the first time an output-feedback approach leveraging physical activity for long-term glucose regulation.