A control engineering approach for optimizing physical activity behavioral interventions

Abstract

This paper presents the use of control engineering principles to optimize mobile and wireless health (mHealth) adaptive behavioral interventions for physical activity based on Social Cognitive Theory (SCT). SCT is a conceptual framework that describes human behavior and has been used in many health behavior interventions. An intervention for physical activity is formulated as a control systems problem relying on a dynamical model of SCT that is developed utilizing fluid analogies. To obtain values for model parameters, system identification experiments are designed including two phases: an initial informative stage followed by an optimized stage that incorporates “patient-friendly” conditions. With the estimated model, a closed-loop intervention is formulated relying on Hybrid Model Predictive Control (HMPC). The HMPC algorithm includes a representation of categorical and discrete constraints that are inherent to behavioral interventions, and the recognition of behavioral initiation and maintenance phases. A simulation study is performed illustrating representative scenarios of the system (in both open and closed-loop).