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Optimizing Behavioral Interventions to Regulate Gestational Weight Gain With Sequential Decision Policies Using

Penghong Guo1, Daniel E Rivera1, Yuwen Dong1

  • 1School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85287-6106 USA.

Computers & Chemical Engineering
|March 28, 2022
PubMed

Excessive gestational weight gain is a significant public health concern that has been the recent focus of control systems-based interventions. Healthy Mom Zone (HMZ) is an intervention study that aims to develop and validate an individually-tailored and "intensively adaptive" intervention to manage weight gain for pregnant women with overweight or obesity using control engineering approaches. This paper presents how Hybrid Model Predictive Control (HMPC) can be used to assign intervention dosages and consequently generate a prescribed intervention with dosages unique to each individuals needs. A Mixed Logical Dynamical (MLD) model enforces the requirements for categorical (discrete-level) doses of intervention components and their sequential assignment into mixed-integer linear constraints. A comprehensive system model that integrates energy balance and behavior change theory, using data from one HMZ participant, is used to illustrate the workings of the HMPC-based control system for the HMZ intervention. Simulations demonstrate the utility of HMPC as a means for enabling optimized complex interventions in behavioral medicine, and the benefits of a HMPC framework in contrast to conventional interventions relying on "IF-THEN" decision rules.

Keywords:
Hybrid Model Predictive Control (HMPC)Mixed Logical Dynamical (MLD) modelsbehavioral interventionsgestational weight gainsequential decision policies

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